Relevant bibliographies by topics / Structural Equations Estimation Model

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Structural Equations Estimation Model'

Author: Grafiati
Published: 18 April 2022
Last updated: 25 April 2022

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Journal articles on the topic "Structural Equations Estimation Model"

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Chipman, John S. "HAAVELMO’S CONTRIBUTIONS TO SIMULTANEOUS-EQUATIONS ESTIMATION." Econometric Theory 31, no. 2 (July 31, 2014): 233–48. http://dx.doi.org/10.1017/s0266466614000280.

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This paper surveys Trygve Haavelmo’s contributions to econometrics. A brief summary of his 1944 monograph is followed by an analysis of the six important papers he contributed during 1943–47. Four of them were devoted to macroeconomic models including estimation of the Keynesian marginal propensity to consume; the first two introduced the methodology of a system of structural equations; the third marked a milestone in econometric method by deriving the reduced form of such a system; and the fourth analyzed the contrast between time-series and cross-section analysis. The fifth (joint with M.A. Girshick) on the demand for food provided a definitive treatment of estimation of demand and supply functions; it carried out the execution of a five-equation structural model of the U.S. economy. The sixth was an interesting policy model of the interrelationship between the agricultural and the rural sector of the economy, which was fitted to U.S. data and addressed to questions of policy.
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Lo, Chi Ho, Wing Kam Fung, and Zhong Yi Zhu. "Structural Parameter Estimation Using Generalized Estimating Equations for Regression Credibility Models." ASTIN Bulletin 37, no. 02 (November 2007): 323–43. http://dx.doi.org/10.2143/ast.37.2.2024070.

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A generalized estimating equations (GEE) approach is developed to estimate structural parameters of a regression credibility model with independent or moving average errors. A comprehensive account is given to illustrate how GEE estimators are worked out within an extended Hachemeister (1975) framework. Evidenced by results of simulation studies, the proposed GEE estimators appear to outperform those given by Hachemeister, and have led to a remarkable improvement in accuracy of the credibility estimators so constructed.
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Lo, Chi Ho, Wing Kam Fung, and Zhong Yi Zhu. "Structural Parameter Estimation Using Generalized Estimating Equations for Regression Credibility Models." ASTIN Bulletin 37, no. 2 (November 2007): 323–43. http://dx.doi.org/10.1017/s0515036100014896.

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A generalized estimating equations (GEE) approach is developed to estimate structural parameters of a regression credibility model with independent or moving average errors. A comprehensive account is given to illustrate how GEE estimators are worked out within an extended Hachemeister (1975) framework. Evidenced by results of simulation studies, the proposed GEE estimators appear to outperform those given by Hachemeister, and have led to a remarkable improvement in accuracy of the credibility estimators so constructed.
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Bernardini Papalia, Rosa, and Enrico Ciavolino. "GME Estimation of Spatial Structural Equations Models." Journal of Classification 28, no. 1 (January 21, 2011): 126–41. http://dx.doi.org/10.1007/s00357-011-9073-0.

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Shina, Arya Fendha Ibnu. "ESTIMASI PARAMETER PADA SISTEM MODEL PERSAMAAN SIMULTAN DATA PANEL DINAMIS DENGAN METODE 2 SLS GMM-AB." MEDIA STATISTIKA 11, no. 2 (December 30, 2018): 79–91. http://dx.doi.org/10.14710/medstat.11.2.79-91.

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Single equation models ignore interdependencies or two-way relationships between response variables. The simultaneous equation model accommodates this two-way relationship form. Two Stage Least Square Generalized Methods of Moment Arellano and Bond (2 SLS GMM-AB) is used to estimate the parameters in the simultaneous system model of dynamic panel data if each structural equation is exactly identified or over identified. In the simultaneous equation system model with dynamic panel data, each structural equation and reduced form is a dynamic panel data regression equation. Estimation of structural equations and reduced form using Ordinary Least Square (OLS) resulted biased and inconsistent estimators. Arellano and Bond GMM method (GMM AB) estimator produces unbiased, consistent, and efficient estimators.The purpose of this paper is to explain the steps of 2 SLS GMM-AB method to estimate parameter in simultaneous equation model with dynamic panel data. Keywords:2 SLS GMM-AB, Arellano and Bond estimator, Dynamic Panel Data, Simultaneous Equations
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Chen, Songnian, Cheng Hsiao, and Liqun Wang. "MEASUREMENT ERRORS AND CENSORED STRUCTURAL LATENT VARIABLES MODELS." Econometric Theory 28, no. 3 (November 25, 2011): 696–703. http://dx.doi.org/10.1017/s0266466611000715.

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We consider censored structural latent variables models where some exogenous variables are subject to additive measurement errors. We demonstrate that overidentification conditions can be exploited to provide natural instruments for the variables measured with errors, and we propose a two-stage estimation procedure. The first stage involves substituting available instruments in lieu of the variables that are measured with errors and estimating the resulting reduced form parameters using consistent censored regression methods. The second stage obtains structural form parameters using the conventional linear simultaneous equations model estimators.
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Suzuki, Hironori, Takashi Nakatsuji, Yordphol Tanaboriboon, and Kiyoshi Takahashi. "Dynamic Estimation of Origin-Destination Travel Time and Flow on a Long Freeway Corridor: Neural Kalman Filter." Transportation Research Record: Journal of the Transportation Research Board 1739, no. 1 (January 2000): 67–75. http://dx.doi.org/10.3141/1739-09.

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A model was formulated for estimating dynamic origin-destination (O-D) travel time and flow on a long freeway with a neural Kalman filter originally developed by the authors. The model predicts O-D travel times and flows simultaneously by using traffic detector data such as link traffic volumes, spot speeds, and off-ramp volumes. The model is based on a Kalman filter that consists of two equations: state and measurement. First, the state and measurement equations of the Kalman filter were modified to consider the influence of traffic states for some previous time steps. Then artificial neural network models were integrated with the Kalman filter to enable nonlinear formulations of the state and measurement equations. Finally, a macroscopic traffic flow simulation model was introduced to simulate traffic states on a freeway in advance and predict traffic variables such as O-D travel times, link traffic volumes, spot speeds, and off-ramp volumes. The new model was compared with a regression Kalman filter in which the state and measurement equations are defined by regression models. The numerical analysis indicated that the new model was capable of estimating nonlinearity of dynamic O-D travel time and flow and helped to improve their estimation precision under free-flow traffic states as well as congested flow states.
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Skeels, Christopher L. "Instrumental Variables Estimation in Misspecified Single Equations." Econometric Theory 11, no. 3 (June 1995): 498–529. http://dx.doi.org/10.1017/s0266466600009385.

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This paper examines the exact sampling behavior of a family of instrumental variables estimators of the coefficients in a single structural equation when the model has been misspecified by the incorrect inclusion or exclusion of variables. It is found that such specification errors can have implications for the structure of the exact results obtained. A brief numerical examination of the analytical results is also provided.
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Hamerle, Alfred, Willi Nagl, and Hermann Singer. "Problems with the estimation of stochastic differential equations using structural equations models." Journal of Mathematical Sociology 16, no. 3 (November 1991): 201–20. http://dx.doi.org/10.1080/0022250x.1991.9990088.

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Hsiao, Cheng, and Qiankun Zhou. "JIVE FOR PANEL DYNAMIC SIMULTANEOUS EQUATIONS MODELS." Econometric Theory 34, no. 6 (November 2, 2017): 1325–69. http://dx.doi.org/10.1017/s0266466617000421.

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We consider the method of moments estimation of a structural equation in a panel dynamic simultaneous equations model under different sample size combinations of cross-sectional dimension, N, and time series dimension, T. Two types of linear transformation to remove the individual-specific effects from the model, first difference and forward orthogonal demeaning, are considered. We show that the Alvarez and Arellano (2003) type GMM estimator under both transformations is consistent only if ${T \over N} \to 0$ as $\left( {N,T} \right) \to \infty $. However, it is asymptotically biased if ${{{T^3}} \over N} \to \kappa \ne 0 < \infty$ as $\left( {N,T} \right) \to \infty $. Since the validity of statistical inference depends critically on whether an estimator is asymptotically unbiased, we suggest a jackknife bias reduction method and derive its limiting distribution. Monte Carlo studies are conducted to demonstrate the importance of using an asymptotically unbiased estimator to obtain valid statistical inference.
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Dissertations / Theses on the topic "Structural Equations Estimation Model"

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Zheng, Xueying, and 郑雪莹. "Robust joint mean-covariance model selection and time-varying correlation structure estimation for dependent data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hub.hku.hk/bib/B50899703.

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In longitudinal and spatio-temporal data analysis, repeated measurements from a subject can be either regional- or temporal-dependent. The correct specification of the within-subject covariance matrix cultivates an efficient estimation for mean regression coefficients. In this thesis, robust estimation for the mean and covariance jointly for the regression model of longitudinal data within the framework of generalized estimating equations (GEE) is developed. The proposed approach integrates the robust method and joint mean-covariance regression modeling. Robust generalized estimating equations using bounded scores and leverage-based weights are employed for the mean and covariance to achieve robustness against outliers. The resulting estimators are shown to be consistent and asymptotically normally distributed. Robust variable selection method in a joint mean and covariance model is considered, by proposing a set of penalized robust generalized estimating equations to estimate simultaneously the mean regression coefficients, the generalized autoregressive coefficients and innovation variances introduced by the modified Cholesky decomposition. The set of estimating equations select important covariate variables in both mean and covariance models together with the estimating procedure. Under some regularity conditions, the oracle property of the proposed robust variable selection method is developed. For these two robust joint mean and covariance models, simulation studies and a hormone data set analysis are carried out to assess and illustrate the small sample performance, which show that the proposed methods perform favorably by combining the robustifying and penalized estimating techniques together in the joint mean and covariance model. Capturing dynamic change of time-varying correlation structure is both interesting and scientifically important in spatio-temporal data analysis. The time-varying empirical estimator of the spatial correlation matrix is approximated by groups of selected basis matrices which represent substructures of the correlation matrix. After projecting the correlation structure matrix onto the space spanned by basis matrices, varying-coefficient model selection and estimation for signals associated with relevant basis matrices are incorporated. The unique feature of the proposed model and estimation is that time-dependent local region signals can be detected by the proposed penalized objective function. In theory, model selection consistency on detecting local signals is provided. The proposed method is illustrated through simulation studies and a functional magnetic resonance imaging (fMRI) data set from an attention deficit hyperactivity disorder (ADHD) study.
published_or_final_version
Statistics and Actuarial Science
Doctoral
Doctor of Philosophy
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Jonnavithula, Siva S. "Development of structural equations models of statewide freight flows." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000278.

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Asgari, Hamidreza. "On the Impacts of Telecommuting over Daily Activity/Travel Behavior: A Comprehensive Investigation through Different Telecommuting Patterns." FIU Digital Commons, 2015. http://digitalcommons.fiu.edu/etd/2182.

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The interest in telecommuting stems from the potential benefits in alleviating traffic congestion, decreasing vehicle miles traveled (VMT), and improving air quality by reducing the necessity for travel between home and the workplace. Despite the potential economic, environmental, and social benefits, telecommuting has not been widely adopted, and there is little consensus on the actual impacts of telecommuting. One of the major hurdles is lack of a sound instrument to quantify the impacts of telecommuting on individuals’ travel behavior. As a result, the telecommuting phenomenon has not received proper attention in most transportation planning and investment decisions, if not completely ignored. This dissertation addresses the knowledge gap in telecommuting studies by examining several factors. First, it proposes a comprehensive outline to reveal and represent the complexity in telecommuting patterns. There are various types of telecommuting engagement, with different impacts on travel outcomes. It is necessary to identify and distinguish between those people for whom telecommuting involves a substitution of work travel and those for whom telecommuting is an ancillary activity. Secondly, it enhances the current modeling framework by supplementing the choice/frequency approach with daily telework dimensions, since the traditional approach fails to recognize the randomness of telecommuting engagement in a daily context. A multi-stage modeling structure is developed, which incorporates choice, frequency, engagement, and commute, as the fundamental dimensions of telecommuting activity. One pioneering perspective of this methodology is that it identifies non-regular telecommuters, who represent a significant share of daily telecommuters. Lastly, advanced statistical modeling techniques are employed to measure the actual impacts of each telecommuting arrangement on travelers’ daily activity-travel behavior, focusing on time-use analysis and work trip departure times. This research provides a systematic and sound instrument that advances the understanding of the benefits and potentials of telecommuting and impacts on travel outcomes. It is expected to facilitate policy and decision makers with higher accuracy and contribute to the better design and analysis of transportation investment decisions.
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Koch, Rainer, Ulrich Julius, Werner Jaross, and Hans-Egbert Schröder. "Estimation of the Heritability of Latent Variables Which Are Included in a Structural Model for Metabolic Syndrome." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-137470.

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In a study looking for risk factors of atherosclerosis in families with combined hyperlipidemia and hypertension, clinical and biochemical data of 1,149 persons were analyzed to develop two hypothetical multivariate scores concerning the degree to which a patient is affected by the metabolic syndrome. The scores are based on a structural model for low-density cholesterol (LDL) and high-density cholesterol (HDL), triglycerides, uric acid, creatinine, glucose, insulin, systolic blood pressure and waist-to-hip ratio. Age, gender and body mass index were used for adjusting all variables. In segregation analyses of 42 pedigrees without using genotype information, estimations of the heritabilities and environmentally caused variance and covariance components were computed for the individual score values of the two latent factors. The first score shows a heritability of 42%; the environment component disappeared. The score mainly reflects the HDL, LDL and triglyceride levels. The second score shows a heritability of 16% with an environment component of 7%. It includes mainly insulin, uric acid and creatinine. In the search for genetic causes, both scores could be a basis for further phenotypic classification of the metabolic syndrome
Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich
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Koch, Rainer, Ulrich Julius, Werner Jaross, and Hans-Egbert Schröder. "Estimation of the Heritability of Latent Variables Which Are Included in a Structural Model for Metabolic Syndrome." Karger, 2001. https://tud.qucosa.de/id/qucosa%3A27735.

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In a study looking for risk factors of atherosclerosis in families with combined hyperlipidemia and hypertension, clinical and biochemical data of 1,149 persons were analyzed to develop two hypothetical multivariate scores concerning the degree to which a patient is affected by the metabolic syndrome. The scores are based on a structural model for low-density cholesterol (LDL) and high-density cholesterol (HDL), triglycerides, uric acid, creatinine, glucose, insulin, systolic blood pressure and waist-to-hip ratio. Age, gender and body mass index were used for adjusting all variables. In segregation analyses of 42 pedigrees without using genotype information, estimations of the heritabilities and environmentally caused variance and covariance components were computed for the individual score values of the two latent factors. The first score shows a heritability of 42%; the environment component disappeared. The score mainly reflects the HDL, LDL and triglyceride levels. The second score shows a heritability of 16% with an environment component of 7%. It includes mainly insulin, uric acid and creatinine. In the search for genetic causes, both scores could be a basis for further phenotypic classification of the metabolic syndrome.
Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.
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Katsikatsou, Myrsini. "Composite Likelihood Estimation for Latent Variable Models with Ordinal and Continuous, or Ranking Variables." Doctoral thesis, Uppsala universitet, Statistiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-188342.

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The estimation of latent variable models with ordinal and continuous, or ranking variables is the research focus of this thesis. The existing estimation methods are discussed and a composite likelihood approach is developed. The main advantages of the new method are its low computational complexity which remains unchanged regardless of the model size, and that it yields an asymptotically unbiased, consistent, and normally distributed estimator. The thesis consists of four papers. The first one investigates the two main formulations of the unrestricted Thurstonian model for ranking data along with the corresponding identification constraints. It is found that the extra identifications constraints required in one of them lead to unreliable estimates unless the constraints coincide with the true values of the fixed parameters. In the second paper, a pairwise likelihood (PL) estimation is developed for factor analysis models with ordinal variables. The performance of PL is studied in terms of bias and mean squared error (MSE) and compared with that of the conventional estimation methods via a simulation study and through some real data examples. It is found that the PL estimates and standard errors have very small bias and MSE both decreasing with the sample size, and that the method is competitive to the conventional ones. The results of the first two papers lead to the next one where PL estimation is adjusted to the unrestricted Thurstonian ranking model. As before, the performance of the proposed approach is studied through a simulation study with respect to relative bias and relative MSE and in comparison with the conventional estimation methods. The conclusions are similar to those of the second paper. The last paper extends the PL estimation to the whole structural equation modeling framework where data may include both ordinal and continuous variables as well as covariates. The approach is demonstrated through an example run in R software. The code used has been incorporated in the R package lavaan (version 0.5-11).
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Bodine, Andrew James. "A Monte Carlo Investigation of Fit Statistic Behavior in Measurement Models Assessed Using Limited-and Full-Information Estimation." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1433412282.

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Vieira, Catarina Augusto Pires. "Motivações rurais, autenticidade e intenções comportamentais dos turistas." Master's thesis, Instituto Superior de Economia e Gestão, 2021. http://hdl.handle.net/10400.5/23353.

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Mestrado Bolonha em Marketing
O desafio é desenvolver estratégias que criem perceções positivas aos turistas, induzindo estímulos para revisitar e recomendar destinos turísticos rurais, contribuindo para a sustentabilidade do mundo rural, para a estabilidade e bem-estar pessoal das comunidades de receção e dos turistas e para a maior coesão territorial. A realização deste desafio alcança-se pela valorização da autenticidade dos destinos rurais. O objetivo da presente dissertação consiste em desenvolver um modelo explicativo da influência da autenticidade existencial nas intenções comportamentais, sendo a autenticidade proposta como um construto mediador na relação entre motivações turísticas rurais e intenções comportamentais. Esta dissertação teve uma abordagem quantitativa, com base na aplicação de um inquérito por questionário a uma amostra não probabilística por conveniência de 399 inquiridos. De acordo com os objetivos propostos, utilizou-se o Modelo de Equações Estruturais com estimação PLS (Partial Least Squares) e foi possível confirmar a importância da autenticidade existencial nas intenções em revisitar e recomendar destinos rurais. Concluiu-se, à posteriori, que a autenticidade existencial desempenha um papel mediador entre motivações turísticas e intenções, mas apenas se aplica aos turistas que são motivados pela busca do relaxamento e da aprendizagem.
The proposed challenge is to develop strategies which create positive impressions in tourists, inducing stimuli so that they may wish to return to touristic rural destinations, as well as recommend them. This will contribute to the sustainability of the rural world, to its stability, and to the personal wellbeing of its hosting communities, which in turn uplifts tourist experience and territorial cohesion. This challenge may be approached by giving increased emphasis to the authenticity of rural destinations. The objective of this dissertation consists in developing a model that explains the influence of existential authenticity in behavioural intentions, considering that authenticity can be defined as a mediating construct in the relationship between rural touristic motivations and behavioural intentions. This dissertation sought a quantitative approach, based on the application of a survey, or questionnaire, to a non-probabilistic sample of 399 respondents. In accordance with the proposed objectives, a Structural Equations estimation Model with the PLS (Partial Least Squares) approach was used, and it was possible to confirm the importance of existential authenticity in the intentions of revisiting and recommending rural destinations. It was concluded, a posteriori, that existential authenticity portrays a mediating role between touristic motivations and intentions, but only in tourists who are motivated by the desire for relaxation and learning.
info:eu-repo/semantics/publishedVersion
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Codd, Casey L. "Nonlinear Structural Equation Models: Estimation and Applications." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1301409131.

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Ciraki, Dario. "Dynamic structural equation models : estimation and interference." Thesis, London School of Economics and Political Science (University of London), 2007. http://etheses.lse.ac.uk/2937/.

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The thesis focuses on estimation of dynamic structural equation models in which some or all variables might be unobservable (latent) or measured with error. Moreover, we consider the situation where latent variables can be measured with multiple observable indicators and where lagged values of latent variables might be included in the model. This situation leads to a dynamic structural equation model (DSEM), which can be viewed as dynamic generalisation of the structural equation model (SEM). Taking the mismeasurement problem into account aims at reducing or eliminating the errors-in-variables bias and hence at minimising the chance of obtaining incorrect coefficient estimates. Furthermore, such methods can be used to improve measurement of latent variables and to obtain more accurate forecasts. The thesis aims to make a contribution to the literature in four areas. Firstly, we propose a unifying theoretical framework for the analysis of dynamic structural equation models. Secondly, we provide analytical results for both panel and time series DSEM models along with the software implementation suggestions. Thirdly, we propose non-parametric estimation methods that can also be used for obtaining starting values in maximum likelihood estimation. Finally, we illustrate these methods on several real data examples demonstrating the capabilities of the currently available software as well as importance of good starting values.
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Books on the topic "Structural Equations Estimation Model"

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Seiichi, Katayama. Estimation of structural change in the import and export equations: An international comparison. Kobe, Japan: Institute of Economic Research, Kobe University of Commerce, 1985.

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Hodoshima, Jiro. Identification and estimation in linear simultaneous equations models with structural change under limited information: Gains by homoskedasticity. Louvain-la-Neuve: CORE, 1985.

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Krishnakumar, Jayalakshmi. Estimation of simultaneous equation models with error components structure. Berlin: Springer Verlag, 1988.

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Krishnakumar, Jayalakshmi. Estimation of simultaneous equation models with error components structure. Berlin: Springer-Verlag, 1988.

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Krishnakumar, Jayalakshmi. Estimation of Simultaneous Equation Models with Error Components Structure. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-45647-3.

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Bock, Hans Georg. Model Based Parameter Estimation: Theory and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Inverse problem theory: Methods for data fitting and model parameter estimation. Amsterdam: Elsevier, 1987.

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Boorman, D. B. A review of the flood studies report rainfall-runoff model parameter estimation equations. [s.l.]: Institute of Hydrology, 1985.

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Babeshko, Lyudmila, Mihail Bich, and Irina Orlova. Econometrics and econometric modeling. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1141216.

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The textbook covers a wide range of issues related to econometric modeling. Regression models are the core of econometric modeling, so the issues of their evaluation, testing of assumptions, adjustment and verification are given a significant place. Various aspects of multiple regression models are included: multicollinearity, dummy variables, and lag structure of variables. Methods of linearization and estimation of nonlinear models are considered. An apparatus for evaluating systems of simultaneous and apparently unrelated equations is presented. Attention is paid to time series models. Detailed solutions of the examples in Excel and the R software environment are included. Meets the requirements of the federal state educational standards of higher education of the latest generation. For undergraduate and graduate students studying in the field of "Economics", the curriculum of which includes the disciplines "Econometrics"," Econometric Modeling","Econometric research".
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1975-, Sims Robert, and Ueltschi Daniel 1969-, eds. Entropy and the quantum II: Arizona School of Analysis with Applications, March 15-19, 2010, University of Arizona. Providence, R.I: American Mathematical Society, 2011.

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Book chapters on the topic "Structural Equations Estimation Model"

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Donaghy, Kieran, Arash Beheshtian, Ziye Zhang, and Benjamin Brown-Steiner. "Estimation of a Continuous-Time Structural-Equation Model of Commodity Flows." In Advances in Spatial Science, 99–137. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78555-0_7.

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Hair, Joseph F., G. Tomas M. Hult, Christian M. Ringle, Marko Sarstedt, Nicholas P. Danks, and Soumya Ray. "The SEMinR Package." In Classroom Companion: Business, 49–74. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80519-7_3.

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AbstractSEMinR is a software package developed for the R statistical environment (R Core Team, 2021). The package includes a user-friendly syntax for creating and estimating structural equation models using estimators such as partial least squares. In this chapter, we introduce the syntax to create, estimate, and report structural equation models using SEMinR. We demonstrate the four steps to specifying and estimating a structural equation model: (1) loading and cleaning the data, (2) specifying the measurement models, (3) specifying the structural model, and (4) estimating, bootstrapping, and summarizing the model. This chapter also describes how to export results and figures from R for professional, publication-quality reporting.
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Krishnakumar, Jayalakshmi. "Presentation of Simultaneous Equations Model with Error Components Structure and Estimation of the Reduced Form." In Lecture Notes in Economics and Mathematical Systems, 47–119. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-45647-3_3.

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Bezruchko, Boris P., and Dmitry A. Smirnov. "Model Equations: Parameter Estimation." In Extracting Knowledge From Time Series, 233–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12601-7_8.

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Hair, Joseph F., G. Tomas M. Hult, Christian M. Ringle, Marko Sarstedt, Nicholas P. Danks, and Soumya Ray. "An Introduction to Structural Equation Modeling." In Classroom Companion: Business, 1–29. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80519-7_1.

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AbstractStructural equation modeling is a multivariate data analysis method for analyzing complex relationships among constructs and indicators. To estimate structural equation models, researchers generally draw on two methods: covariance-based SEM (CB-SEM) and partial least squares SEM (PLS-SEM). Whereas CB-SEM is primarily used to confirm theories, PLS represents a causal–predictive approach to SEM that emphasizes prediction in estimating models, whose structures are designed to provide causal explanations. PLS-SEM is also useful for confirming measurement models. This chapter offers a concise overview of PLS-SEM’s key characteristics and discusses the main differences compared to CB-SEM. The chapter also describes considerations when using PLS-SEM and highlights situations that favor its use compared to CB-SEM.
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Friswell, M. I., and J. E. Mottershead. "Estimation Techniques." In Finite Element Model Updating in Structural Dynamics, 78–97. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-015-8508-8_5.

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Snoke, Joshua, Timothy Brick, and Aleksandra Slavković. "Accurate Estimation of Structural Equation Models with Remote Partitioned Data." In Privacy in Statistical Databases, 190–209. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45381-1_15.

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Groetsch, Charles W. "Parameter Estimation in Differential Equations: Model Identification." In Inverse Problems in the Mathematical Sciences, 41–66. Wiesbaden: Vieweg+Teubner Verlag, 1993. http://dx.doi.org/10.1007/978-3-322-99202-4_3.

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Datsyshyn, Oleksandra, and Volodymyr Panasyuk. "Calculation Model for Estimation of Cyclic Contact Lifetime of Body with Cracks." In Structural Integrity, 25–64. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23069-2_2.

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Pal, Manisha, Nripes K. Mandal, and Bikas K. Sinha. "Growth Models for Repeated Measurement Mixture Experiments: Optimal Designs for Parameter Estimation and Growth Prediction." In Advances in Growth Curve and Structural Equation Modeling, 81–94. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0980-9_6.

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Conference papers on the topic "Structural Equations Estimation Model"

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Thompson, Thomas J. "Spherical Compliant Model for Vibration Estimation and Control." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0577.

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Abstract Proposed space missions involve large structures which must maintain precise dimensional tolerances during dynamic maneuvers. In order to attenuate disturbances in the many modes of vibration of such structures, active and passive vibration control has been proposed. Passive control is to be achieved by placing viscous or viscoelastic members in a structure to absorb energy, while active control similarly could involve structural members (struts) capable of sensing axial displacement and exerting axial control force. With conventional modal analysis, the effect of a control element on a system is computed by summing its influence on many immutable modes. Since changes in mode shape must be described by this summation, truncation of higher modes results in inaccuracies. The compliant model of vibration to be presented accurately accounts for the effects of locally-acting control elements without inclusion of high-frequency modes. The motion of each spring-mass system representing a structural mode is modified by a control element in series with another stiffness inherent to the structure for that mode and control position. In order to predict the influence of several control elements or dampers on closely-spaced modes, the compliant models for those modes are integrated into a spherical model in which one lumped mass is acted upon by orthogonal modal stiffnesses. In the spherical model, control elements influent the lumped mass from orientations determined by mode participation factors. The resulting equations of motion are stated in standard state-space form. To test accuracy, the compliant model is used to predict eigenvalue shifts due to springs and dampers acting upon an axially-vibrating rod, and the spherical model is used to predict damping accurately in a lumped-mass system with closely-spaced modes.
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Li, Yong. "Notice of Retraction: Linear Structural Equation Model and Sas Procedure for Parameter Estimation." In 2009 International Forum on Information Technology and Applications (IFITA). IEEE, 2009. http://dx.doi.org/10.1109/ifita.2009.572.

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Luo, Yongchao, Jianjun Wang, Siyu Chen, and Xiaocong Cui. "A parameter estimation method for structural equation model based on generalized maximum entropy." In 2012 Third International Conference on Intelligent Control and Information Processing (ICICIP). IEEE, 2012. http://dx.doi.org/10.1109/icicip.2012.6391494.

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Silva, Clodoaldo J., and Mohammed F. Daqaq. "On Utilizing Approximate Modal Shapes to Estimate the Effective Nonlinearity of a Structural Mode." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-71113.

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This effort investigates the accuracy of estimating the effective nonlinearity of a given vibration mode using approximate modal shapes. As an example, the problem of approximating the modal effective nonlinearities of a linearly-tapered cantilever beam (along the width) is considered. This example was intentionally selected because the linear eigenvalue problem cannot be solved analytically for the exact eigenfrequencies and actual linear mode shapes of the structure, which permits investigating the influence of approximating the mode shapes on the effective nonlinearity. The nonlinear partial differential equation governing the beam’s motion is first discretized into an infinite set of nonlinear ordinary differential equations. The method of multiple scales is then utilized to obtain an approximate analytical expression for the effective nonlinearity which depends on the assumed mode shapes used in the series discretization. To approximate the mode shapes, three methods were utilized: i) a crude approach which directly utilizes the linear modes of a regular (untapered) cantilever beam to estimate the effective nonlinearity, ii) a finite element approach wherein the structural modes are obtained in ANSYS, then fitted into orthonormal polynomial curves while minimizing the least square error in calculating the eigenfrequencies, and iii) a Rayleigh-Ritz approach which utilizes a set of orthonormal trial basis functions to construct the structural mode shapes as a linear combination of the trial functions used. A comparison among the three methods for eight different taperings reveals that, while the modal frequencies are well-approximated yielding less than 2% deviation among the three methods, there is a huge discrepancy in approximating the nonlinear coefficients including the effective nonlinearity. This leads to the conclusion that convergence of the eigenfrequencies is not sufficient for accurate estimation of the nonlinear parameters.
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Donato, Gustavo H. B., and Claudio Ruggieri. "Estimation Procedures for J and CTOD Fracture Parameters Using Three-Point Bend Specimens." In 2006 International Pipeline Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/ipc2006-10165.

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This work presents the development of J and CTOD estimation procedures for deep and shallow cracked bend specimens based upon plastic eta factors and rotational factors. The techniques considered include: i) estimating J and CTOD from plastic work and ii) estimating CTOD from the plastic rotational factor. The primary objective is to derive estimation techniques which are applicable to determine J and CTOD fracture parameters for a wide range of a/W-ratios and material flow properties. Very detailed non-linear finite element analyses for plane-strain models provide the evolution of load with increased load-line displacement and crack mouth opening displacement which are required for the estimation procedure. Laboratory testing of a structural steel using shallow and deep crack bend specimens provide the data needed to determine the CTOD-values for the material based upon the proposed methodology. These fracture toughness values are compared against the results obtained based upon the estimation equations given by BS 7448. The present analyses, when taken together with previous studies, provide a fairly extensive body of results which serve to determine parameters J and CTOD using bend specimens with varying geometries.
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Rahman, Sharif, Noel N. Nemeth, and John P. Gyekenyesi. "Life Prediction and Reliability Analysis of Ceramic Structures Under Combined Static and Cyclic Fatigue." In ASME 1998 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/98-gt-569.

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This paper presents a computational methodology for life prediction and time-dependent reliability analysis of ceramic structures under combined effects of static and cyclic fatigue. It involves (1) a crack-growth equation representing damage contributions from both static and cyclic fatigue, (2) a multivariate nonlinear regression model for performing parameter estimation from fatigue data generated by small specimens, and (3) the Batdorf model for structural reliability analysis. A linear superposition of crack-growth rates obtained from the Power-law and Walker-law equations was used. The model assumes that the time-dependent and cycle-dependent crack growth formulation exponents are identical, and that loading frequency and amplitude do not vary over time. For the parameter estimation, the regression was performed using nonlinear least squares and a modified Levenberg-Marquardt algorithm. This methodology was implemented into the integrated design code named CARES/Life (Ceramics Analysis and Reliability Evaluation of Structures/Life). A numerical example is presented to illustrate the parameter estimation component of this methodology. The results suggest that the predicted stress-life curves based on the proposed model can correlate better with experimental data when compared with either Power-law or the Walker-law models individually.
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Bhouri, Mohamed Aziz. "Model-Order-Reduction Approach for Structural Health Monitoring of Large Deployed Structures With Localized Operational Excitations." In ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/detc2021-70375.

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Abstract We present a simulation-based classification approach for large deployed structures with localized operational excitations. The method extends the two-level Port-Reduced Reduced-Basis Component (PR-RBC) technique to provide faster solution estimation to the hyperbolic partial differential equation of time-domain elastodynamics with a moving load. Time-domain correlation function-based features are built in order to train classifiers such as Artificial Neural Networks and Support-Vector Machines and perform damage detection. The method is tested on a bridge-shaped structure with a moving vehicle (playing the role of a digital twin) in order to detect cracks’ existence. Such problem has 45 parameters and shows the merits of the two-level PR-RBC approach and of the correlation function-based features in the context of operational excitations, other nuisance parameters and added noise. The quality of the classification task is enhanced by the sufficiently large synthetic training dataset and the accuracy of the numerical solutions, reaching test classification errors below 0.1% for disjoint training set of size 7 × 103 and test set of size 3 × 103. Effects of the numerical solutions accuracy and of the sensors locations on the classification errors are also studied, showing the robustness of the proposed approach and the importance of constructing a rich and accurate representation of possible healthy and unhealthy states of interest.
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Li, Yixian, Limin Sun, and Wei Zhang. "Structural response reconstruction using inclinometer and velocimeter." In IABSE Congress, New York, New York 2019: The Evolving Metropolis. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2019. http://dx.doi.org/10.2749/newyork.2019.1977.

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<p>This paper proposes a structural dynamic response reconstruction algorithm using inclinometer and velocimeter, combining in-situ measured data with finite element model. Using a small number of inclination and velocity data, the dynamic deflection, rotation, and strain at any position of a structure can be estimated. Firstly, static structural deformation estimation method is introduced as the base. The key content is to solve an underdetermined static equation using partial least square regression and calculate equivalent nodal force. By rewriting dynamic balance equation into state space, an equivalent static balance equation is obtained. Use partial least square regression to solve this equation and compute time histogram of equivalent nodal force, in which dynamic distortion exists. Accordingly, a frequency response-based time interval correction method is proposed to correct the dynamic distortion and is validated to be effective. Finally, numerical simulation is adopted to validate accuracy and robustness of the algorithm through changing parameters including sampling time interval, input frequency components, model parameters and introducing measurement noise. All results have demonstrated that the algorithm is of good adaptability to various changes and maintains high accuracy.</p>
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Arif, Abul Fazal M., Ahmad S. Al-Omari, Anwar K. Sheikh, Yagoub Al-Nassar, and M. Anis. "Estimation of Residual Stress in Spiral Welded Pipe: Regression and Numerical Model." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-87703.

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Double submerged spiral-welded pipe (SWP) is used extensively throughout the world for large-diameter pipelines. Fabrication-induced residual stresses in spiral welded pipe have received increasing attention in gas, oil and petrochemical industry. Several studies reported in the literature verify the critical role of residual stresses in the failure of these pipes. Therefore, it is important that such stresses are accounted for in safety assessment procedures such as the British R6 and BS7910. This can be done only when detailed information on the residual stress distribution in the component is known. In industry, residual stresses in spiral welded pipe are measured experimentally by means of destructive techniques known as Ring Splitting Test. In this study, statistical analysis and linear-regression modeling were used to study the effect of several structural, material and welding parameters on ring splitting test opening for spiral welded pipes. The experimental results were employed to develop an appropriate regression equation, and to predict the residual stress on the spiral welded pipes. It was found that the developed regression equation explains 36.48% of the variability in the ring opening. In the second part, a 3-D finite element model is presented to perform coupled-field analysis of the welding of spiral pipe. Using this model, temperature as well as stress fields in the region of the weld edges is predicted.
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Young, Bruce A., Rick J. Olson, and Matthew Kerr. "Advances in COD Equations — Circumferential Through-Wall Cracks." In ASME 2012 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/pvp2012-78181.

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Non-linear fracture mechanics equations for through-wall cracks in a pipe are used to analyze piping systems for either critical flaw size or critical loading conditions as part of probabilistic Leak-Before-Break (LBB) failure analyses under the eXtremely Low Probability of Rupture (xLPR) program co-sponsored by the U.S. Nuclear Regulatory Commission (US NRC) and the Electric Power Research Institute (EPRI). The xLPR analysis techniques use a large number of independent analysis solutions to determine an overall assessment of system failure probability. As part of the assessment, each independent solution requires the solution of the crack opening displacement (COD) for a through-wall crack (TWC) in a pipe under the prescribed loading conditions. The COD evaluations are then used to determine a leak rate for the given load conditions and crack sizes. The purpose of this paper is to present results which advance the start-of-the-art for determining the elastic-plastic functions for crack opening displacements (COD) for a TWC in a pipe system under combined tension and bending loads. The current method used to determine COD in xLPR, a blending of tension and bending solution from the GE-EPRI Handbook, determined the continuum equations using structural finite element analyses with shell type elements. Since that body of work was undertaken, there have been significant advancements in computing capability such that structural finite element analyses with three-dimension continuum elements are currently feasible. The use of continuum elements provides several advantages over shell elements; such as, the ability to elicit details of variation in the COD through the thickness of the pipe wall and to apply pressure to the crack face due to the internal pipe pressure. Furthermore, the original GE-EPRI solutions were limited for the case of combined tension and bending loads. The existing GE-EPRI solutions for combined loading conditions are limited to pipe radius-to-wall thickness (R/t) ratios of 10 or greater, typical of those piping systems found in the boiling water reactor (BWR) fleet. For the PWR piping systems of concern today, which are subject to primary water stress corrosion cracking (PWSCC), the R/t ratios are typically 5 or less. As a result of the limitations with the existing GE-EPRI method for predicting COD, Battelle and US NRC staff set out to develop a comprehensive COD prediction tool for combined loadings which would be applicable to both PWR as well as BWR piping. This effort involved a matrix of over 1,200 finite element analyses for a full range of pipe sizes, R/t ratios, through-wall crack (TWC) lengths, and internal pipe pressures. It is anticipated that there will be several parts to this effort. Part I, discussed in this paper, focuses on the development of the model and the initial investigation into the elastic- and elastic-plastic fitting functions for the prediction of COD (i.e., the V and h functions). Future parts of this effort will focus on such issues as the effect of restraint of pressure induced bending on COD, the effect of weld residual stresses on COD, J-Integral estimation schemes, and development of variable crack-face pressure.
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Reports on the topic "Structural Equations Estimation Model"

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Calsamglia, Caterina, Chao Fu, and Maia Güell. Structural Estimation of a Model of School Choices: the Boston Mechanism vs. Its Alternatives. Cambridge, MA: National Bureau of Economic Research, May 2018. http://dx.doi.org/10.3386/w24588.

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Kimhi, Ayal, Barry Goodwin, Ashok Mishra, Avner Ahituv, and Yoav Kislev. The dynamics of off-farm employment, farm size, and farm structure. United States Department of Agriculture, September 2006. http://dx.doi.org/10.32747/2006.7695877.bard.

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Objectives: (1) Preparing panel data sets for both the United States and Israel that contain a rich set of farm attributes, such as size, specialization, and output composition, and farmers’ characteristics such as off-farm employment status, education, and family composition. (2) Developing an empirical framework for the joint analysis of all the endogenous variables of interest in a dynamic setting. (3) Estimating simultaneous equations of the endogenous variables using the panel data sets from both countries. (4) Analyzing, using the empirical results, the possible effects of economic policies and institutional changes on the dynamics of the farm sector. An added objective is analyzing structural changes in farm sectors in additional countries. Background: Farm sectors in developed countries, including the U.S. and Israel, have experienced a sharp decline in their size and importance during the second half of the 20th century. The overall trend is towards fewer and larger farms that rely less on family labor. These structural changes have been a reaction to changes in technology, in government policies, and in market conditions: decreasing terms of trade, increasing alternative opportunities, and urbanization pressures. As these factors continue to change, so does the structure of the agricultural sector. Conclusions: We have shown that all major dimensions of structural changes in agriculture are closely interlinked. These include farm efficiency, farm scale, farm scope (diversification), and off-farm labor. We have also shown that these conclusions hold and perhaps even become stronger whenever dynamic aspects of structural adjustments are explicitly modeled using longitudinal data. While the results vary somewhat in the different applications, several common features are observed for both the U.S. and Israel. First, the trend towards the concentration of farm production in a smaller number of larger farm enterprises is likely to continue. Second, at the micro level, increased farm size is negatively associated with increased off-farm labor, with the causality going both ways. Third, the increase in farm size is mostly achieved by diversifying farm production into additional activities (crops or livestock). All these imply that the farm sector converges towards a bi-modal farm distribution, with some farms becoming commercial while the remaining farm households either exit farming altogether or continue producing but rely heavily on off-farm income. Implications: The primary scientific implication of this project is that one should not analyze a specific farm attribute in isolation. We have shown that controlling for the joint determination of the various farm and household attributes is crucial for obtaining meaningful empirical results. The policy implications are to some extent general but could be different in the two countries. The general implication is that farm policy is an important determinant of structural changes in the farm sector. For the U.S., we have shown the different effects of coupled and decoupled (direct) farm payments on the various farm attributes, and also shown that it is important to take into account the joint farm-household decisions in order to conduct a meaningful policy analysis. Only this kind of analysis explains the indirect effect of direct farm payments on farm production decisions. For Israel, we concluded that farm policy (or lack of farm policy) has contributed to the fast structural changes we observed over the last 25 years. The sharp change of direction in farm policy that started in the early 1980s has accelerated structural changes that could have been smoother otherwise. These accelerated structural changes most likely lead to welfare losses in rural areas.
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Keith, B., A. Apostolatos, A. Kodakkal, R. Rossi, R. Tosi, B. Wohlmuth, and C. Soriano. D2.3. Adjoint-based error estimation routines. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.022.

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This document presents a simple and ecient strategy for adaptive mesh renement (AMR) and a posteriori error estimation for the transient incompressible Navier{Stokes equations. This strategy is informed by the work of Prudhomme and Oden [22, 23] as well as modern goal-oriented methods such as [5]. The methods described in this document have been implemented in the Kratos Multiphysics software and uploaded to https://zenodo.org [27].1 This document includes: A review of the state-of-the-art in solution-oriented and goal-oriented AMR. The description of a 2D benchmark model problem of immediate relevance to the objectives of the ExaQUte project. The denition and a brief mathematical summary of the error estimator(s). The results obtained. A description of the API.
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Over, Thomas, Riki Saito, Andrea Veilleux, Padraic O’Shea, Jennifer Sharpe, David Soong, and Audrey Ishii. Estimation of Peak Discharge Quantiles for Selected Annual Exceedance Probabilities in Northeastern Illinois. Illinois Center for Transportation, June 2016. http://dx.doi.org/10.36501/0197-9191/16-014.

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This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions. The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, regional skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The skew coefficient values for each streamgage were then computed as the variance-weighted average of at-site and regional skew coefficients. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter. This report also provides: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at ungaged sites and to improve flood-quantile estimates at and near a gaged site; (2) the urbanization-adjusted annual maximum peak discharges and peak discharge quantile estimates at streamgages from 181 watersheds including the 117 study watersheds and 64 additional watersheds in the study region that were originally considered for use in the study but later deemed to be redundant. The urbanization-adjustment equations, spatial regression equations, and peak discharge quantile estimates developed in this study will be made available in the web-based application StreamStats, which provides automated regression-equation solutions for user-selected stream locations. Figures and tables comparing the observed and urbanization-adjusted peak discharge records by streamgage are provided at http://dx.doi.org/10.3133/sir20165050 for download.
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Lubowa, Nasser, Zita Ekeocha, Stephen Robert Byrn, and Kari L. Clase. Pharmaceutical Industry in Uganda: A Review of the Common GMP Non-conformances during Regulatory Inspections. Purdue University, December 2021. http://dx.doi.org/10.5703/1288284317442.

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The prevalence of substandard medicines in Africa is high but not well documented. Low and Middle-Income Countries (LMICs) are likely to face considerable challenges with substandard medications. Africa faces inadequate drug regulatory practices, and in general, compliance with Good Manufacturing Practices (GMP) in most of the pharmaceutical industries is lacking. The majority of pharmaceutical manufacturers in developing countries are often overwhelmed by the GMP requirements and therefore are unable to operate in line with internationally acceptable standards. Non-conformances observed during regulatory inspections provide the status of the compliance to GMP requirements. The study aimed to identify the GMP non-conformances during regulatory inspections and gaps in the production of pharmaceuticals locally manufactured in Uganda by review of the available 50 GMP reports of 21 local pharmaceutical companies in Uganda from 2016. The binary logistic generalized estimating equations (GEE) model was applied to estimate the association between odds of a company failing to comply with the GMP requirements and non-conformances under each GMP inspection parameter. Analysis using dummy estimation to linear regression included determination of the relationship that existed between the selected variables (GMP inspection parameters) and the production capacity of the local pharmaceutical industry. Oral liquids, external liquid preparations, powders, creams, and ointments were the main categories of products manufactured locally. The results indicated that 86% of the non-conformances were major, 11% were minor, and 3% critical. The majority of the non-conformances were related to production (30.1%), documentation (24.5%), and quality control (17.6%). Regression results indicated that for every non-conformance under premises, equipment, and utilities, there was a 7-fold likelihood of the manufacturer failing to comply with the GMP standards (aOR=6.81, P=0.001). The results showed that major non-conformances were significantly higher in industries of small scale (B=6.77, P=0.02) and medium scale (B=8.40, P=0.04), as compared to those of large scale. This study highlights the failures in quality assurance systems and stagnated GMP improvements in these industries that need to be addressed by the manufacturers with support from the regulator. The addition of risk assessment to critical production and quality control operations and establishment of appropriate corrective and preventive actions as part of quality management systems are required to ensure that quality pharmaceuticals are manufactured locally.
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Gur, Amit, Edward Buckler, Joseph Burger, Yaakov Tadmor, and Iftach Klapp. Characterization of genetic variation and yield heterosis in Cucumis melo. United States Department of Agriculture, January 2016. http://dx.doi.org/10.32747/2016.7600047.bard.

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Project objectives: 1) Characterization of variation for yield heterosis in melon using Half-Diallele (HDA) design. 2) Development and implementation of image-based yield phenotyping in melon. 3) Characterization of genetic, epigenetic and transcriptional variation across 25 founder lines and selected hybrids. The epigentic part of this objective was modified during the course of the project: instead of characterization of chromatin structure in a single melon line through genome-wide mapping of nucleosomes using MNase-seq approach, we took advantage of rapid advancements in single-molecule sequencing and shifted the focus to Nanoporelong-read sequencing of all 25 founder lines. This analysis provides invaluable information on genome-wide structural variation across our diversity 4) Integrated analyses and development of prediction models Agricultural heterosis relates to hybrids that outperform their inbred parents for yield. First generation (F1) hybrids are produced in many crop species and it is estimated that heterosis increases yield by 15-30% globally. Melon (Cucumismelo) is an economically important species of The Cucurbitaceae family and is among the most important fleshy fruits for fresh consumption Worldwide. The major goal of this project was to explore the patterns and magnitude of yield heterosis in melon and link it to whole genome sequence variation. A core subset of 25 diverse lines was selected from the Newe-Yaar melon diversity panel for whole-genome re-sequencing (WGS) and test-crosses, to produce structured half-diallele design of 300 F1 hybrids (MelHDA25). Yield variation was measured in replicated yield trials at the whole-plant and at the rootstock levels (through a common-scion grafted experiments), across the F1s and parental lines. As part of this project we also developed an algorithmic pipeline for detection and yield estimation of melons from aerial-images, towards future implementation of such high throughput, cost-effective method for remote yield evaluation in open-field melons. We found extensive, highly heritable root-derived yield variation across the diallele population that was characterized by prominent best-parent heterosis (BPH), where hybrids rootstocks outperformed their parents by 38% and 56 % under optimal irrigation and drought- stress, respectively. Through integration of the genotypic data (~4,000,000 SNPs) and yield analyses we show that root-derived hybrids yield is independent of parental genetic distance. However, we mapped novel root-derived yield QTLs through genome-wide association (GWA) analysis and a multi-QTLs model explained more than 45% of the hybrids yield variation, providing a potential route for marker-assisted hybrid rootstock breeding. Four selected hybrid rootstocks are further studied under multiple scion varieties and their validated positive effect on yield performance is now leading to ongoing evaluation of their commercial potential. On the genomic level, this project resulted in 3 layers of data: 1) whole-genome short-read Illumina sequencing (30X) of the 25 founder lines provided us with 25 genome alignments and high-density melon HapMap that is already shown to be an effective resource for QTL annotation and candidate gene analysis in melon. 2) fast advancements in long-read single-molecule sequencing allowed us to shift focus towards this technology and generate ~50X Nanoporesequencing of the 25 founders which in combination with the short-read data now enable de novo assembly of the 25 genomes that will soon lead to construction of the first melon pan-genome. 3) Transcriptomic (3' RNA-Seq) analysis of several selected hybrids and their parents provide preliminary information on differentially expressed genes that can be further used to explain the root-derived yield variation. Taken together, this project expanded our view on yield heterosis in melon with novel specific insights on root-derived yield heterosis. To our knowledge, thus far this is the largest systematic genetic analysis of rootstock effects on yield heterosis in cucurbits or any other crop plant, and our results are now translated into potential breeding applications. The genomic resources that were developed as part of this project are putting melon in the forefront of genomic research and will continue to be useful tool for the cucurbits community in years to come.
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NUMERICAL ANALYSIS AND EVALUATION OF EFFECTIVE SLAB WIDTH OF COMPOSITE CONTINUOUS BEAMS WITH SEMI-RIGID JOINT. The Hong Kong Institute of Steel Construction, December 2021. http://dx.doi.org/10.18057/ijasc.2021.17.4.1.

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The characterization of the structural behavior of composite beams is directly affected by the determination of the effective slab width. Various codes propose their own definitions of the effective width based on the beam span and the slab width parameters. However, the evaluation of the effective width may be influenced by other parameters. The aim of this work is to determine the most important factors affecting effective width for continuous composite beams with semi-rigid joints using numerical simulations. A three-dimensional finite element model of a composite continuous beam using explicit-solver available in ABAQUS is developed. The proposed model is validated through comparisons to available experimental results. A modified model is proposed based on the so-validated model to study the influence of the composite beam-column joint stiffness on the effective width. Then, both numerical models are used to perform an extensive parametric study to investigate the influence of various parameters on the estimation of the effective slab width. The influence of slab width, the shear connection degree, and composite joint stiffness are particularly analyzed to find out the most important parameters influencing the effective width so that simplified equations for the calculation of the effective slab width are proposed.
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A SIMPLE METHOD FOR A RELIABLE MODELLING OF THE NONLINEAR BEHAVIOUR OF BOLTED CONNECTIONS IN STEEL LATTICE TOWERS. The Hong Kong Institute of Steel Construction, March 2022. http://dx.doi.org/10.18057/ijasc.2022.18.1.6.

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The behaviour of bolted connections in steel lattice transmission line towers affects their load-bearing capacity and failure mode. Bolted connections are commonly modelled as pinned or fixed joints, but their behaviour lies between these two extremes and evolves in a nonlinear manner. Accordingly, an accurate finite element modelling of the structural response of complete steel lattice towers requires the consideration of various nonlinear phenomena involved in bolted connexions, such as bolt slippage. In this study, a practical method is proposed for the modelling of the nonlinear response of steel lattice tower connections involving one or multiple bolts. First, the local load-deformation behaviour of single-bolt lap connections is evaluated analytically depending on various geometric and material parameters and construction details. Then, the predicted nonlinear behaviour for a given configuration serves as an input to a 2D/3D numerical model of the entire assembly of plates in which the bolted joints are represented as discrete elements. For comparison purposes, an extensive experimental study comprising forty-four tests were conducted on steel plates assembled with one or two bolts. This approach is also extended to simulate the behaviour of assemblies including four bolts and the obtained results are checked against experimental datasets from the literature. The obtained results show that the proposed method can predict accurately the response of a variety of multi-bolt connections. A potential application of the strategy developed in this paper could be in the numerical modelling of full-scale steel lattice towers, particularly for a reliable estimation of the displacements.
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