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Relevant bibliographies by topics / Random effect model

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Academic literature on the topic 'Random effect model'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 April 2022

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Journal articles on the topic "Random effect model"

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Huang, Hung-Yu, and Wen-Chung Wang. "The Random-Effect DINA Model." Journal of Educational Measurement 51, no. 1 (March 2014): 75–97. http://dx.doi.org/10.1111/jedm.12035.

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Šiaulys, Jonas, and Rokas Puišys. "Survival with Random Effect." Mathematics 10, no. 7 (March 29, 2022): 1097. http://dx.doi.org/10.3390/math10071097.

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The article focuses on mortality models with a random effect applied in order to evaluate human mortality more precisely. Such models are called frailty or Cox models. The main assertion of the paper shows that each positive random effect transforms the initial hazard rate (or density function) to a new absolutely continuous survival function. In particular, well-known Weibull and Gompertz hazard rates and corresponding survival functions are analyzed with different random effects. These specific models are presented with detailed calculations of hazard rates and corresponding survival functions. Six specific models with a random effect are applied to the same data set. The results indicate that the accuracy of the model depends on the data under consideration.

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Kalhori, Lida, and Mohsen Mohhamadzadeh. "Spatial Beta Regression Model with Random Effect." Journal of Statistical Research of Iran 13, no. 2 (March 1, 2017): 215–30. http://dx.doi.org/10.18869/acadpub.jsri.13.2.215.

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Wang, Wen-Chung, and Shiu-Lien Wu. "The Random-Effect Generalized Rating Scale Model." Journal of Educational Measurement 48, no. 4 (December 2011): 441–56. http://dx.doi.org/10.1111/j.1745-3984.2011.00154.x.

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Kayid, M., S. Izadkhah, and D. ALmufarrej. "Random Effect Additive Mean Residual Life Model." IEEE Transactions on Reliability 65, no. 2 (June 2016): 860–66. http://dx.doi.org/10.1109/tr.2015.2491600.

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Motarjem, K., M. Mohammadzadeh, and A. Abyar. "Geostatistical survival model with Gaussian random effect." Statistical Papers 61, no. 1 (June 20, 2017): 85–107. http://dx.doi.org/10.1007/s00362-017-0922-8.

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Spineli, Loukia M., and Nikolaos Pandis. "Fixed-effect versus random-effects model in meta-regression analysis." American Journal of Orthodontics and Dentofacial Orthopedics 158, no. 5 (November 2020): 770–72. http://dx.doi.org/10.1016/j.ajodo.2020.07.016.

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Wen, Limin, Jing Fang, Guoping Mei, and Xianyi Wu. "Optimal credibility estimation of random parameters in hierarchical random effect linear model." Journal of Systems Science and Complexity 28, no. 5 (July 30, 2015): 1058–69. http://dx.doi.org/10.1007/s11424-015-3202-5.

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Hernández, Freddy, and Viviana Giampaoli. "The Impact of Misspecified Random Effect Distribution in a Weibull Regression Mixed Model." Stats 1, no. 1 (May 31, 2018): 48–76. http://dx.doi.org/10.3390/stats1010005.

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Mixed models are useful tools for analyzing clustered and longitudinal data. These models assume that random effects are normally distributed. However, this may be unrealistic or restrictive when representing information of the data. Several papers have been published to quantify the impacts of misspecification of the shape of the random effects in mixed models. Notably, these studies primarily concentrated their efforts on models with response variables that have normal, logistic and Poisson distributions, and the results were not conclusive. As such, we investigated the misspecification of the shape of the random effects in a Weibull regression mixed model with random intercepts in the two parameters of the Weibull distribution. Through an extensive simulation study considering six random effect distributions and assuming normality for the random effects in the estimation procedure, we found an impact of misspecification on the estimations of the fixed effects associated with the second parameter σ of the Weibull distribution. Additionally, the variance components of the model were also affected by the misspecification.

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ADACHI, Kohei. "A Random Effect Model in Metric Multidimensional Unfolding." Kodo Keiryogaku (The Japanese Journal of Behaviormetrics) 27, no. 1 (2000): 12–23. http://dx.doi.org/10.2333/jbhmk.27.12.

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Dissertations / Theses on the topic "Random effect model"

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Kwong, Grace Pui Sze. "Model misspecification and random effect models in survival analysis." Thesis, University of Warwick, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398729.

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Cao, Hongmei. "A random effect model with quality score for meta-analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ58754.pdf.

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Cheng, Yang. "Maximum likelihood estimation and computation in a random effect factor model." College Park, Md. : University of Maryland, 2004. http://hdl.handle.net/1903/1782.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2004.
Thesis research directed by: Mathematics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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Choi, Ga Eun, and Stephanie Galonja. "The Euro Effect on Trade : The Trade Effect of the Euro on non-EMU and EMU Members." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Economics, Finance and Statistics, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-20114.

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The purpose of this paper is to investigate how the changes in trade values are affected by the implementation of the euro currency. We study the EU members, including 11 EMU members and 3 non-EMU members (Sweden, Denmark and the United Kingdom). The empirical analysis is conducted by using a modified version of the standard gravity model. Our core findings can be summarized into two parts. First, the euro effect on trade which is estimated by the euro-dummy coefficient reflects an adverse influence by the euro creation on trade values for the first two years of the implementation on all our sample countries. It leads us to a conclusion that there is no significant improvement of trade in the year of implementation. These results do not change when a time trend variable is added to evaluate the robustness of the model. Our primary interpretation is that the euro creation does not have an immediate impact on trade but it is rather gradual as countries need time to adapt to a new currency. It is connected to our second finding that the negative influence of the euro implementation is not permanent but eventually initiates positive outcomes on trade values over time, thus concluding that the euro implementation has had gradual impact on both EMU and non-EMU members.

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HE, Ran. "Carry-over and interaction effects of different hand-milking techniques and milkers on milk." Thesis, Uppsala universitet, Statistiska institutionen, 1986. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-154641.

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The main idea of this thesis is studying the importance of the carry-over effects and interaction effects in statistical models. To investigate it, a hand-milking experiment in Burkina Faso was studied. In many no electricity access countries, such as Burkina Faso, the amount of milk and milk compositions are still highly relying on hand-milking techniques and milkers. Moreover, the time effects also plays a important role in stockbreeding system. Therefore, falling all effects, carry-over effects and interaction effects into a linear mixed effects model, it is concluded that the carry-over effects of milker and hand-milking techniques cannot be neglected, and the interaction effects among hand-milking techniques, different milkers, days and periods can be substantial.

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Puschmann, Martin. "Anderson transitions on random Voronoi-Delaunay lattices." Doctoral thesis, Universitätsbibliothek Chemnitz, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-231900.

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The dissertation covers phase transitions in the realm of the Anderson model of localization on topologically disordered Voronoi-Delaunay lattices. The disorder is given by random connections which implies correlations due to the restrictive lattice construction. Strictly speaking, the system features "strong anticorrelation", which is responsible for quenched long-range fluctuations of the coordination number. This attribute leads to violations of universal behavior in various system, e.g. Ising and Potts model, and to modifications of the Harris and the Imry-Ma criteria. In general, these exceptions serve to further understanding of critical phenomena. Hence, the question arises whether such deviations also occur in the realm of the Anderson model of localization in combination with random Voronoi-Delaunay lattice. For this purpose, four cases, which are distinguished by the spatial dimension of the systems and by the presence or absence of a magnetic field, are investigated by means of two different methods, i.e the multifractal analysis and the recursive Green function approach. The behavior is classified by the existence and type of occurring phase transitions and by the critical exponent v of the localization length. The results for the four cases can be summarized as follows. In two-dimensional systems, no phase transitions occur without a magnetic field, and all states are localized as a result of topological disorder. The behavior changes under the influence of the magnetic field. There are so-called quantum Hall transitions, which are phase changes between two localized regions. For low magnetic field strengths, the resulting exponent v ≈ 2.6 coincides with established values in literature. For higher strengths, an increased value, v ≈ 2.9, was determined. The deviations are probably caused by so-called Landau level coupling, where electrons scatter between different Landau levels. In contrast, the principle behavior in three-dimensional systems is equal in both cases. Two localization-delocalization transitions occur in each system. For these transitions the exponents v ≈ 1.58 and v ≈ 1.45 were determined for systems in absence and in presence of a magnetic field, respectively. This behavior and the obtained values agree with known results, and thus no deviation from the universal behavior can be observed
Diese Dissertation behandelt Phasenübergange im Rahmen des Anderson-Modells der Lokalisierung in topologisch ungeordneten Voronoi-Delaunay-Gittern. Die spezielle Art der Unordnung spiegelt sich u.a. in zufälligen Verknüpfungen wider, welche aufgrund der restriktiven Gitterkonstruktion miteinander korrelieren. Genauer gesagt zeigt das System eine "starke Antikorrelation", die dafür sorgt, dass langreichweitige Fluktuationen der Verknüpfungszahl unterdrückt werden. Diese Eigenschaft hat in anderen Systemen, z.B. im Ising- und Potts-Modell, zur Abweichung vom universellen Verhalten von Phasenübergängen geführt und bewirkt eine Modifikation von allgemeinen Aussagen, wie dem Harris- and Imry-Ma-Kriterium. Die Untersuchung solcher Ausnahmen dient zur Weiterentwicklung des Verständnisses von kritischen Phänomenen. Somit stellt sich die Frage, ob solche Abweichungen auch im Anderson-Modell der Lokalisierung unter Verwendung eines solchen Gitters auftreten. Dafür werden insgesamt vier Fälle, welche durch die Dimension des Gitters und durch die An- bzw. Abwesenheit eines magnetischen Feldes unterschieden werden, mit Hilfe zweier unterschiedlicher Methoden, d.h. der Multifraktalanalyse und der rekursiven Greensfunktionsmethode, untersucht. Das Verhalten wird anhand der Existenz und Art der Phasenübergänge und anhand des kritischen Exponenten v der Lokalisierungslänge unterschieden. Für die vier Fälle lassen sich die Ergebnisse wie folgt zusammenfassen. In zweidimensionalen Systemen treten ohne Magnetfeld keine Phasenübergänge auf und alle Zustände sind infolge der topologischen Unordnung lokalisiert. Unter Einfluss des Magnetfeldes ändert sich das Verhalten. Es kommt zur Ausformung von Landau-Bändern mit sogenannten Quanten-Hall-Übergängen, bei denen ein Phasenwechsel zwischen zwei lokalisierten Bereichen auftritt. Für geringe Magnetfeldstärken stimmen die erzielten Ergebnisse mit den bekannten Exponenten v ≈ 2.6 überein. Allerdings wurde für stärkere magnetische Felder ein höherer Wert, v ≈ 2.9, ermittelt. Die Abweichungen gehen vermutlich auf die zugleich gestiegene Unordnungsstärke zurück, welche dafür sorgt, dass Elektronen zwischen verschiedenen Landau-Bändern streuen können und so nicht das kritische Verhalten eines reinen Quanten-Hall-Überganges repräsentieren. Im Gegensatz dazu ist das Verhalten in dreidimensionalen Systemen für beide Fälle ähnlich. Es treten in jedem System zwei Phasenübergänge zwischen lokalisierten und delokalisierten Bereichen auf. Für diese Übergänge wurde der Exponent v ≈ 1.58 ohne und v ≈ 1.45 unter Einfluss eines magnetischen Feldes ermittelt. Dieses Verhalten und die jeweils ermittelten Werte stimmen mit bekannten Ergebnissen überein. Eine Abweichung vom universellen Verhalten wird somit nicht beobachtet

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Ren, Weijia. "Impact of Design Features for Cross-Classified Logistic Models When the Cross-Classification Structure Is Ignored." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1322538958.

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Wang, Yu. "A study on the type I error rate and power for generalized linear mixed model containing one random effect." Kansas State University, 2017. http://hdl.handle.net/2097/35301.

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Master of Science
Department of Statistics
Christopher Vahl
In animal health research, it is quite common for a clinical trial to be designed to demonstrate the efficacy of a new drug where a binary response variable is measured on an individual experimental animal (i.e., the observational unit). However, the investigational treatments are applied to groups of animals instead of an individual animal. This means the experimental unit is the group of animals and the response variable could be modeled with the binomial distribution. Also, the responses of animals within the same experimental unit may then be statistically dependent on each other. The usual logit model for a binary response assumes that all observations are independent. In this report, a logit model with a random error term representing the group of animals is considered. This is model belongs to a class of models referred to as generalized linear mixed models and is commonly fit using the SAS System procedure PROC GLIMMIX. Furthermore, practitioners often adjust the denominator degrees of freedom of the test statistic produced by PROC GLIMMIX using one of several different methods. In this report, a simulation study was performed over a variety of different parameter settings to compare the effects on the type I error rate and power of two methods for adjusting the denominator degrees of freedom, namely “DDFM = KENWARDROGER” and “DDFM = NONE”. Despite its reputation for fine performance in linear mixed models with normally distributed errors, the “DDFM = KENWARDROGER” option tended to perform poorly more often than the “DDFM = NONE” option in the logistic regression model with one random effect.

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Mingolini, Riccardo. "Investimenti in lobby: Un modello per stimare il loro impatto sull'azienda." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/13291/.

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In questo elaborato di tesi verrà analizzata l’attitudine di una azienda ad investire in lobbying, misurato attraverso varie variabili importanti per la stessa quali ad esempio il capitale, il reddito netto dell’impresa, il numero degli impiegati (et simila) e il loro impatto scoraggiante o incentivante rispetto alla nostra variabile dipendente. Cercheremo infine di trovare un modello che approssima in modo sostanziale suddette dipendenze e variabili, in modo da tracciare un filo logico e matematico fra la nostra variabile dipendente Y ( investimento in lobbying) e le nostre variabili indipendenti X cioè gli indici e le variabili in valore monetario importanti per definire una azienda e il suo settore di appartenenza (SIC CODE).

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Oberhardt, Tobias. "A micromechanical model for the nonlinearity of microcracks in random distributions and their effect on higher harmonic Rayleigh wave generation." Thesis, Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54365.

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This research investigates the modeling of randomly distributed surface-breaking microcracks and their effects on higher harmonic generation in Rayleigh surface waves. The modeling is based on micromechanical considerations of rough surface contact. The nonlinear behavior of a single microcrack is described by a hyperelastic effective stress-strain relationship. Finite element simulations of nonlinear wave propagation in a solid with distributed microcracks are performed. The evolution of fundamental and second harmonic amplitudes along the propagation distance is studied and the acoustic nonlinearity parameter is calculated. The results show that the nonlinearity parameter increases with crack density and root mean square roughness of the crack faces. While, for a dilute concentration of microcracks, the increase in acoustic nonlinearity is proportional to the crack density, this is not valid for higher crack densities, as the microcracks start to interact. Finally, it is shown that odd higher harmonic generation in Rayleigh surface waves due to sliding crack faces introduces a friction nonlinearity.

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Books on the topic "Random effect model"

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Dunson, David B., ed. Random Effect and Latent Variable Model Selection. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-76721-5.

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Cao, Hongmei. A random effect model with quality score for meta-analysis. Ottawa: National Library of Canada, 2001.

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Lee, Youngjo. Generalized Linear Models with Random Effects. Second edition. | Boca Raton, Florida : CRC Press, [2017] |: Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9781315119953.

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Linear and nonlinear models: Fixed effects, random effects, and mixed models. Berlin: Walter de Gruyter, 2006.

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Grafarend, Erik. Linear and Nonlinear Models: Fixed effects, random effects, and total least squares. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Arulampalam, Wiji. A note on estimated coefficients in random effects probit models. Coventry: University of Warwick, Department of Economics, 1998.

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Yi, Qilong. Random effects and AR(1) models in longitudinal data analysis. Ottawa: National Library of Canada, 2000.

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Yi, Qian. Investigating the dynamic effects of counterfeits with a random changepoint simultaneous equation model. Cambridge, MA: National Bureau of Economic Research, 2011.

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Mealli, Fabrizia. Occupational pensions and job mobility in Britain: Estimation of a random-effects competing risks model. Leicester: University of Leicester, Department of Economics, 1993.

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1973-, Warzel Simone, ed. Random operators: Disorder effects on quantum spectra and dynamics. Providence, Rhode Island: American Mathematical Society, 2015.

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Book chapters on the topic "Random effect model"

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Kinney, Satkartar K., and David B. Dunson. "Bayesian Model Uncertainty in Mixed Effects Models." In Random Effect and Latent Variable Model Selection, 37–62. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-76721-5_3.

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Lee, Sik-Yum, and Xin-Yuan Song. "Bayesian Model Comparison of Structural Equation Models." In Random Effect and Latent Variable Model Selection, 121–50. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-76721-5_6.

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Ghosh, Joyee, and David B. Dunson. "Bayesian Model Selection in Factor Analytic Models." In Random Effect and Latent Variable Model Selection, 151–63. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-76721-5_7.

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Crainiceanu, Ciprian M. "Likelihood Ratio Testing for Zero Variance Components in Linear Mixed Models." In Random Effect and Latent Variable Model Selection, 3–17. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-76721-5_1.

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Zhang, Daowen, and Xihong Lin. "Variance Component Testing in Generalized Linear Mixed Models for Longitudinal/Clustered Data and other Related Topics." In Random Effect and Latent Variable Model Selection, 19–36. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-76721-5_2.

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Cai, Bo, and David B. Dunson. "Bayesian Variable Selection in Generalized Linear Mixed Models." In Random Effect and Latent Variable Model Selection, 63–91. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-76721-5_4.

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Bentler, Peter M., and Jiajuan Liang. "A Unified Approach to Two-Level Structural Equation Models and Linear Mixed Effects Models." In Random Effect and Latent Variable Model Selection, 95–119. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-76721-5_5.

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Vannucci, Giulia, Anna Gottard, Leonardo Grilli, and Carla Rampichini. "Random effects regression trees for the analysis of INVALSI data." In Proceedings e report, 29–34. Florence: Firenze University Press, 2021. http://dx.doi.org/10.36253/978-88-5518-304-8.07.

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Mixed or multilevel models exploit random effects to deal with hierarchical data, where statistical units are clustered in groups and cannot be assumed as independent. Sometimes, the assumption of linear dependence of a response on a set of explanatory variables is not plausible, and model specification becomes a challenging task. Regression trees can be helpful to capture non-linear effects of the predictors. This method was extended to clustered data by modelling the fixed effects with a decision tree while accounting for the random effects with a linear mixed model in a separate step (Hajjem & Larocque, 2011; Sela & Simonoff, 2012). Random effect regression trees are shown to be less sensitive to parametric assumptions and provide improved predictive power compared to linear models with random effects and regression trees without random effects. We propose a new random effect model, called Tree embedded linear mixed model, where the regression function is piecewise-linear, consisting in the sum of a tree component and a linear component. This model can deal with both non-linear and interaction effects and cluster mean dependencies. The proposal is the mixed effect version of the semi-linear regression trees (Vannucci, 2019; Vannucci & Gottard, 2019). Model fitting is obtained by an iterative two-stage estimation procedure, where both the fixed and the random effects are jointly estimated. The proposed model allows a decomposition of the effect of a given predictor within and between clusters. We will show via a simulation study and an application to INVALSI data that these extensions improve the predictive performance of the model in the presence of quasi-linear relationships, avoiding overfitting, and facilitating interpretability.

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Elishakoff, Isaac. "Random Vibration of a Vehicle Model." In Dramatic Effect of Cross-Correlations in Random Vibrations of Discrete Systems, Beams, Plates, and Shells, 51–62. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40394-2_3.

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Sperling, L. H. "The “Katz Effect” on the Random Coil Model for Polymer Chains." In Pioneers in Polymer Science, 41–46. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2407-9_4.

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Conference papers on the topic "Random effect model"

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OKI, KAZUYA, HAJIME MASE, and TERRY S. HEDGES. "ENERGY BALANCE EQUATION MODEL WITH DIFFRACTION EFFECT FOR RANDOM WAVES." In Proceedings of the 29th International Conference. World Scientific Publishing Company, 2005. http://dx.doi.org/10.1142/9789812701916_0070.

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Yin, J., S. H. Ng, and K. M. Ng. "Kriging model with modified nugget effect for random simulation with heterogeneous variances." In 2008 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2008. http://dx.doi.org/10.1109/ieem.2008.4738165.

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Ma, Zhuanglin, Honglu Zhang, Rui Qiao, and Yang Yang. "Modeling Traffic Accident Frequency on a Freeway Using the Random Effect Negative Binomial Model." In 15th COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784479292.278.

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Zhou, Xianbo, and Kui-Wai Li. "The effects of openness and indigeneity on Growth: Evidence from nonparametric panel data model with two-way random effect." In 2011 International Conference on E-Business and E-Government (ICEE). IEEE, 2011. http://dx.doi.org/10.1109/icebeg.2011.5882239.

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Li, Zhifeng, Liangzhi Cao, Hongchun Wu, Chenghui Wan, and Tianliang Hu. "Effects of Applying the Implicit Particle Fuel Model for Pebble-Bed Reactors." In 2016 24th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/icone24-60382.

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In the pebble-bed high temperature gas-cooled reactor, there exist randomly located TRISO coated fuel particles in the pebbles and randomly located pebbles in the core, which is known as the double stochastic heterogeneity. In the previous research, the regular lattice pattern was used to approximately simulate the pebble unit cells because the difficulties in modeling the randomly located TRISO geometric. This work aimed at to quantify the stochastic effect of high-temperature gas cooled pebble-bed reactor unit cells, and in view of the strong ability to carry out the accurate simulation of random media, the implicit particle fuel model of Monte Carlo method is applied to analyze to the difference between regular distribution and random distribution. Infinite multiplication factors of the pebble-bed reactor unite cells were calculated by the implicit particle fuel model and simple cube regular lattice pattern at different TRISO packing factor from 0.5%–50%. The results showed that the simple cube regular lattice pattern underestimates the infinite multiplication factors for most packing fractions, but overrates the infinite multiplication factors when the packing fraction is very low.

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Adam, Fia Fridayanti, Anang Kurnia, I. Gusti Putu Purnaba, and I. Wayan Mangku. "Prediction of Number of Claims using Poisson Linear Mixed Model with AR(1) random effect." In Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia. EAI, 2020. http://dx.doi.org/10.4108/eai.2-8-2019.2290464.

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ZAPPERI, STEFANO, HANS J. HERRMANN, and STÉPHANE ROUX. "EFFECT OF DAMAGE ON THE ROUGHNESS OF PLANAR CRACKS: THE CASE OF THE RANDOM FUSE MODEL." In International Workshop and Collection of Articles Honoring Professor Antonio Coniglio on the Occasion of his 60th Birthday. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812778109_0034.

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Chernomordik, Victor V., Amir H. Gandjbakhche, Jeremy C. Hebden, and Giovanni Zaccanti. "Random walk model of the effect of lateral boundaries on time-resolved measurements in optical tomography." In BiOS '99 International Biomedical Optics Symposium, edited by Britton Chance, Robert R. Alfano, and Bruce J. Tromberg. SPIE, 1999. http://dx.doi.org/10.1117/12.356804.

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Myrhaug, Dag, Carl Trygve Stansberg, and Hanne Therese Wist. "Aspects of Nonlinear Random Wave Kinematics." In ASME 2002 21st International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2002. http://dx.doi.org/10.1115/omae2002-28205.

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Statistics of the nonlinear free surface elevation as well as the nonlinear random wave kinematics in terms of the horizontal velocity component in arbitrary water depth are addressed. Two different methods are considered: a simplified analytical approach based on second-order Stokes wave theory including the sum-frequency effect only, and a second-order random wave model including both sum-frequency and difference-frequency effects. The paper compares results for the statistics of the nonlinear free surface, and the consequences of neglecting the difference-frequency effect in the first method are discussed.

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Beirow, Bernd, Arnold Kühhorn, Felix Figaschewsky, and Jens Nipkau. "Effect of Mistuning and Damping on the Forced Response of a Compressor Blisk Rotor." In ASME Turbo Expo 2015: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/gt2015-42036.

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The forced response of an E3E-type high pressure compressor blisk front rotor is analyzed with regard to intentional mistuning and its robustness towards additional random mistuning. Both a chosen alternating mistuning pattern and artificial mistuning patterns optimized concerning the forced response are considered. Focusing on three different blade modes, subset of nominal system mode-based reduced order models are employed to compute the forced response. The disk remains unchanged while the Young’s modulus of each blade is used to define the particular mistuning pattern. The well established aerodynamic influence coefficient technique is employed to model aeroelastic coupling and hence to consider the strongly mode- and inter blade phase angle-dependent aerodynamic damping contribution. It has been found that a reduction of the maximum forced response beyond that of the tuned reference can be achieved for particular mistuning patterns and all modes considered. This implies an exciting engine order which would cause a low nodal diameter mode in case of a tuned blisk. At best a nearly 50% reduction of maximum response magnitudes is computed for the fundamental bending mode and large mistuning. The solution proved to be robust towards additional random mistuning of reasonable magnitude, which is of particular interest with regard to a potential technical realization. In case of small mistuning as assumed for the first torsion and the longitudinal bending mode the advantage of achieving response magnitudes beyond the tuned reference gets lost indeed, if random mistuning is superimposed. However, mostly a lower response level is calculated compared to responses obtained from models adjusted to mistuning determined by experiment.

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Reports on the topic "Random effect model"

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Gautier, Eric, and Stefan Hoderlein. A triangular treatment effect model with random coefficients in the selection equation. Institute for Fiscal Studies, December 2012. http://dx.doi.org/10.1920/wp.cem.2012.3912.

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Zhang, Yongping, Wen Cheng, and Xudong Jia. Enhancement of Multimodal Traffic Safety in High-Quality Transit Areas. Mineta Transportation Institute, February 2021. http://dx.doi.org/10.31979/mti.2021.1920.

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Numerous extant studies are dedicated to enhancing the safety of active transportation modes, but very few studies are devoted to safety analysis surrounding transit stations, which serve as an important modal interface for pedestrians and bicyclists. This study bridges the gap by developing joint models based on the multivariate conditionally autoregressive (MCAR) priors with a distance-oriented neighboring weight matrix. For this purpose, transit-station-centered data in Los Angeles County were used for model development. Feature selection relying on both random forest and correlation analyses was employed, which leads to different covariate inputs to each of the two jointed models, resulting in increased model flexibility. Utilizing an Integrated Nested Laplace Approximation (INLA) algorithm and various evaluation criteria, the results demonstrate that models with a correlation effect between pedestrians and bicyclists perform much better than the models without such an effect. The joint models also aid in identifying significant covariates contributing to the safety of each of the two active transportation modes. The research results can furnish transportation professionals with additional insights to create safer access to transit and thus promote active transportation.

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Sigeti, David Edward, and Scott Alan Vander Wiel. Doubly-Hierarchical One-Way Random Effects Model: Multivariate Data. Office of Scientific and Technical Information (OSTI), October 2016. http://dx.doi.org/10.2172/1329823.

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Weidner, Martin, Hyungsik Roger Moon, and Matthew Shum. Estimation of random coefficients logit demand models with interactive fixed effects. Institute for Fiscal Studies, March 2012. http://dx.doi.org/10.1920/wp.cem.2012.0812.

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Moon, Hyungsik Roger, Matthew Shum, and Martin Weidner. Estimation of random coefficients logit demand models with interactive fixed effects. The IFS, February 2017. http://dx.doi.org/10.1920/wp.cem.2017.1217.

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Shum, Matthew, Hyungsik Roger Moon, and Martin Weidner. Estimation of random coefficients logit demand models with interactive fixed effects. Institute for Fiscal Studies, April 2014. http://dx.doi.org/10.1920/wp.cem.2014.2014.

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Qian, Yi, and Hui Xie. Investigating the Dynamic Effects of Counterfeits with a Random Changepoint Simultaneous Equation Model. Cambridge, MA: National Bureau of Economic Research, January 2011. http://dx.doi.org/10.3386/w16692.

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Ukkusuri, Satish, Lu Ling, Tho V. Le, and Wenbo Zhang. Performance of Right-Turn Lane Designs at Intersections. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317277.

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Right-turn lane (RTL) crashes are among the most key contributors to intersection crashes in the US. Different right turn lanes based on their design, traffic volume, and location have varying levels of crash risk. Therefore, engineers and researchers have been looking for alternative ways to improve the safety and operations for right-turn traffic. This study investigates the traffic safety performance of the RTL in Indiana state based on multi-sources, including official crash reports, official database, and field study. To understand the RTL crashes' influencing factors, we introduce a random effect negative binomial model and log-linear model to estimate the impact of influencing factors on the crash frequency and severity and adopt the robustness test to verify the reliability of estimations. In addition to the environmental factors, spatial and temporal factors, intersection, and RTL geometric factors, we propose build environment factors such as the RTL geometrics and intersection characteristics to address the endogeneity issues, which is rarely addressed in the accident-related research literature. Last, we develop a case study with the help of the Indiana Department of Transportation (INDOT). The empirical analyses indicate that RTL crash frequency and severity is mainly influenced by turn radius, traffic control, and other intersection related factors such as right-turn type and speed limit, channelized type, and AADT, acceleration lane and AADT. In particular, the effects of these factors are different among counties and right turn lane roadway types.

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Pettit, Chris, and D. Wilson. A physics-informed neural network for sound propagation in the atmospheric boundary layer. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/41034.

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We describe what we believe is the first effort to develop a physics-informed neural network (PINN) to predict sound propagation through the atmospheric boundary layer. PINN is a recent innovation in the application of deep learning to simulate physics. The motivation is to combine the strengths of data-driven models and physics models, thereby producing a regularized surrogate model using less data than a purely data-driven model. In a PINN, the data-driven loss function is augmented with penalty terms for deviations from the underlying physics, e.g., a governing equation or a boundary condition. Training data are obtained from Crank-Nicholson solutions of the parabolic equation with homogeneous ground impedance and Monin-Obukhov similarity theory for the effective sound speed in the moving atmosphere. Training data are random samples from an ensemble of solutions for combinations of parameters governing the impedance and the effective sound speed. PINN output is processed to produce realizations of transmission loss that look much like the Crank-Nicholson solutions. We describe the framework for implementing PINN for outdoor sound, and we outline practical matters related to network architecture, the size of the training set, the physics-informed loss function, and challenge of managing the spatial complexity of the complex pressure.

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Sadowski, Dieter. Board-Level Codetermination in Germany - The Importance and Economic Impact of Fiduciary Duties. Association Inter-University Centre Dubrovnik, May 2021. http://dx.doi.org/10.53099/ntkd4304.

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The empirical accounts of the costs and benefits of quasi-parity codetermined supervisory boards, a very special German institution, have long been inconclusive. A valid economic analysis of a particular legal regulation must take the legal specificities seriously, otherwise it will be easily lost in economic fictions of functional equivalence. At its core the corporate actor “supervisory board” has no a priori objective function to be maximised – the corner stone of the theory of the firm – but its objective function will only be brought about a posteriori – should negotiations result in an agreement (E. Fraenkel). With this understanding,the paper presents six recent quasi-experimental studies on the economic (dis) advantageousness of the German codetermination laws that try to follow the rules of causal inference despite the lack of random variation. By and large they refute the hold-up model of codetermination by showing positive or nonnegative effects even on shareholder wealth – and a far-reaching improvement of the well-being of the core workforce. In conclusion, indications are offered that the shareholder primacy movement has only weakened, but not dissolved the “Deutschland AG”.

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