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Relevant bibliographies by topics / Structural models

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Academic literature on the topic 'Structural models'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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Journal articles on the topic "Structural models"

1

Jaguljnjak Lazarević, Antonia, Mario Uroš, and Ana Čengija. "FUNDAMENTAL MODELS OF STRUCTURAL STABILITY." Rudarsko-geološko-naftni zbornik 32, no. 2 (2017): 37–46. http://dx.doi.org/10.17794/rgn.2017.2.5.

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Arellano-Valle, R. B., and H. Bolfarine. "Elliptical structural models." Communications in Statistics - Theory and Methods 25, no. 10 (1996): 2319–41. http://dx.doi.org/10.1080/03610929608831841.

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Sánchez, Brisa N., Esben Budtz-Jørgensen, Louise M. Ryan, and Howard Hu. "Structural Equation Models." Journal of the American Statistical Association 100, no. 472 (2005): 1443–55. http://dx.doi.org/10.1198/016214505000001005.

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De Stavola, Bianca L., and Rhian M. Daniel. "Marginal Structural Models." Epidemiology 23, no. 2 (2012): 233–37. http://dx.doi.org/10.1097/ede.0b013e318245847e.

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Amemiya, Takeshi. "Structural duration models." Journal of Statistical Planning and Inference 49, no. 1 (1996): 39–52. http://dx.doi.org/10.1016/0378-3758(95)00029-1.

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Sarkisov, Gari N. "Structural models of water." Uspekhi Fizicheskih Nauk 176, no. 8 (2006): 833. http://dx.doi.org/10.3367/ufnr.0176.200608b.0833.

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Vallat, Brinda, Benjamin Webb, John Westbrook, et al. "Archiving Integrative Structural Models." Biophysical Journal 120, no. 3 (2021): 266a. http://dx.doi.org/10.1016/j.bpj.2020.11.1702.

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Mueller, Charles W., Kenneth A. Bollen, and J. Scott Long. "Testing Structural Equation Models." Contemporary Sociology 23, no. 1 (1994): 160. http://dx.doi.org/10.2307/2074955.

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Clogg, Clifford C., Kenneth A. Bollen, and J. Scott Long. "Testing Structural Equation Models." Social Forces 73, no. 3 (1995): 1161. http://dx.doi.org/10.2307/2580595.

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Dillon, William R., Kenneth A. Bollen, and J. Scott Long. "Testing Structural Equation Models." Journal of Marketing Research 33, no. 3 (1996): 374. http://dx.doi.org/10.2307/3152134.

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Dissertations / Theses on the topic "Structural models"

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Lievin-Lieven, Nicholas Andrew John. "Validation of structural dynamic models." Thesis, Imperial College London, 1990. http://hdl.handle.net/10044/1/46413.

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Adhikari, Sondipon. "Damping models for structural vibration." Thesis, University of Cambridge, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.620975.

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Fonseca, Jose Manuel Rios. "Uncertainty in structural dynamic models." Thesis, Swansea University, 2005. https://cronfa.swan.ac.uk/Record/cronfa42563.

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Modelling of uncertainty increases trust in analysis tools by providing predictions with confidence levels, produces more robust designs, and reduces design cycle time/cost by reducing the amount of experimental verification and validation that is required. However, uncertainty-based methods are more complex and computationally expensive than their deterministic counterparts, the characterisation of uncertainties is a non-trivial task, and the industry feels comfortable with the traditional design methods. In this work the three most popular uncertainty propagation methods (Monte Carlo simulat

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Creamer, Nelson Glenn. "Identification of linear structural models." Diss., Virginia Polytechnic Institute and State University, 1987. http://hdl.handle.net/10919/53631.

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With a great amount of research currently being aimed towards dynamic analysis and control of very large, flexible structures, the need for accurate knowledge of the properties of a structure in terms of the mass, damping, and stiffness matrices is of extreme importance. Typical problems associated with existing structural model identification methods are: (i) non-unique solutions may be obtained when utilizing only free-response measurements (unless some parameters are fixed at their nominal values), (ii) convergence may be difficult to achieve if the initial estimate of the parameters is not

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Cerqueira, Pedro Henrique Ramos. "Structural equation models applied to quantitative genetics." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-05112015-145419/.

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Causal models have been used in different areas of knowledge in order to comprehend the causal associations between variables. Over the past decades, the amount of studies using these models have been growing a lot, especially those related to biological systems where studying and learning causal relationships among traits are essential for predicting the consequences of interventions in such system. Graph analysis (GA) and structural equation modeling (SEM) are tools used to explore such associations. While GA allows searching causal structures that express qualitatively how variables are cau

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Grafe, Henning. "Model updating of large structural dynamics models using measured response functions." Thesis, Imperial College London, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325047.

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Valeinis, Janis. "Confidence bands for structural relationship models." Doctoral thesis, [S.l.] : [s.n.], 2007. http://webdoc.sub.gwdg.de/diss/2007/valeinis.

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De, Antonio Liedo David. "Structural models for macroeconomics and forecasting." Doctoral thesis, Universite Libre de Bruxelles, 2010. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210142.

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This Thesis is composed by three independent papers that investigate<p>central debates in empirical macroeconomic modeling.<p><p>Chapter 1, entitled “A Model for Real-Time Data Assessment with an Application to GDP Growth Rates”, provides a model for the data<p>revisions of macroeconomic variables that distinguishes between rational expectation updates and noise corrections. Thus, the model encompasses the two polar views regarding the publication process of statistical agencies: noise versus news. Most of the studies previous studies that analyze data revisions are based<p>on the classical no

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Konarski, Roman. "Sensitivity analysis for structural equation models." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq22893.pdf.

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Gungor, Murat Kahraman. "Structural models for large software systems." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2006. http://proquest.umi.com/login?COPT=REJTPTU0NWQmSU5UPTAmVkVSPTI=&clientId=3739.

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Books on the topic "Structural models"

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Westland, J. Christopher. Structural Equation Models. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12508-0.

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Westland, J. Christopher. Structural Equation Models. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16507-3.

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Fieldhouse, John. Biochemical structural models. Witmehá Productions, 1989.

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Fieldhouse, John. Biochemical structural models. 2nd ed. Witmehá Productions, 1993.

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Barry, Hilson, ed. Basic structural behaviour: Understanding structures from models. T. Telford, 1993.

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Godehardt, Erhard. Graphs as Structural Models. Vieweg+Teubner Verlag, 1988. http://dx.doi.org/10.1007/978-3-322-96310-9.

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A, Bollen Kenneth, and Long J. Scott, eds. Testing structural equation models. Sage Publications, 1993.

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University College Dublin. School of Architecture. Structures models. University College Dublin, School of Architecture, 1998.

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Fernández-Villaverde, Jesús. How structural are structural parameters? National Bureau of Economic Research, 2007.

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Stronge, W. J. Dynamic models for structural plasticity. Springer Verlag, 1993.

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Book chapters on the topic "Structural models"

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Albuquerque, Paulo, and Bart J. Bronnenberg. "Structural Models." In International Series in Quantitative Marketing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53469-5_7.

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Galiani, Sebastian, and Juan Pantano. "Structural Models." In Handbook of Labor, Human Resources and Population Economics. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-57365-6_52-1.

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Rots, J. G. "Numerical models in DIANA." In Structural Masonry. CRC Press, 2021. http://dx.doi.org/10.1201/9781003077961-3.

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Hilbert, Sven, and Matthias Stadler. "Structural Equation Models." In Encyclopedia of Personality and Individual Differences. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-24612-3_1285.

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Gómez, Víctor. "Multivariate Structural Models." In Linear Time Series with MATLAB and OCTAVE. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20790-8_7.

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Plassmann, Engelbert. "Structural ECM Models." In Contributions to Economics. Physica-Verlag HD, 2003. http://dx.doi.org/10.1007/978-3-642-57336-1_4.

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Bauldry, Shawn. "Structural Equation Models." In Encyclopedia of Gerontology and Population Aging. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-69892-2_566-1.

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Rosenblum, Michael. "Marginal Structural Models." In Targeted Learning. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9782-1_9.

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Raghunathan, Trivellore, Patricia A. Berglund, and Peter W. Solenberger. "Structural Equation Models." In Multiple Imputation in Practice. Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9781315154275-7.

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Urban, Dean L. "Structural Equation Models." In Landscape Ecology. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-72251-6_7.

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Conference papers on the topic "Structural models"

1

BENAROYA, HAYM, and HOWARD FLEISHER. "Probabilistic aircraft structural dynamics models." In 32nd Structures, Structural Dynamics, and Materials Conference. American Institute of Aeronautics and Astronautics, 1991. http://dx.doi.org/10.2514/6.1991-921.

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SMITH, SUZANNE, and CHRISTOPHER BEATTIE. "Secant-method adjustment for structural models." In 30th Structures, Structural Dynamics and Materials Conference. American Institute of Aeronautics and Astronautics, 1989. http://dx.doi.org/10.2514/6.1989-1278.

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Kordt, M., H. Lusebrink, and G. Schullerus. "Nonlinear model reduction of structural dynamic aircraft models." In 41st Structures, Structural Dynamics, and Materials Conference and Exhibit. American Institute of Aeronautics and Astronautics, 2000. http://dx.doi.org/10.2514/6.2000-1757.

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Sacks, Michael S. "Tissue-Level Structural Constitutive Models." In ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-1925.

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Abstract A fundamental goal in constitutive modeling is the ability to predict the mechanical behavior of a material under a generalized loading state. To achieve this goal, rigorous experimentation involving all relevant deformations is necessary to obtain both the form and material constants of a strain-energy density function. For both natural biological tissues and tissue-derived soft biomaterials, there exist many physiological, surgical, and medical device applications where rigorous constitutive models are required. Although able to fit the biaxial data well, phenomenological models can

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Enelund, Mikael, and Peter Olsson. "Damping described by fading memory models." In 36th Structures, Structural Dynamics and Materials Conference. American Institute of Aeronautics and Astronautics, 1995. http://dx.doi.org/10.2514/6.1995-1181.

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HOLLKAMP, J., and S. BATILL. "Time series models for nonlinear systems." In 30th Structures, Structural Dynamics and Materials Conference. American Institute of Aeronautics and Astronautics, 1989. http://dx.doi.org/10.2514/6.1989-1197.

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BARBERO, E., and S. SONTI. "Micromechanical models for pultruded composite beams." In 32nd Structures, Structural Dynamics, and Materials Conference. American Institute of Aeronautics and Astronautics, 1991. http://dx.doi.org/10.2514/6.1991-1045.

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Hasselman, Timothy, Jon Chrostowski, and Timothy Ross. "Propagation of modeling uncertainty through structural dynamic models." In 35th Structures, Structural Dynamics, and Materials Conference. American Institute of Aeronautics and Astronautics, 1994. http://dx.doi.org/10.2514/6.1994-1316.

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HAJELA, P., and L. BERKE. "Neurobiological Computational Models in Structural Analysis and Design." In 31st Structures, Structural Dynamics and Materials Conference. American Institute of Aeronautics and Astronautics, 1990. http://dx.doi.org/10.2514/6.1990-1133.

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CRAWLEY, EDWARD, and ERIC ANDERSON. "Detailed models of piezoceramic actuation of beams." In 30th Structures, Structural Dynamics and Materials Conference. American Institute of Aeronautics and Astronautics, 1989. http://dx.doi.org/10.2514/6.1989-1388.

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Reports on the topic "Structural models"

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Batman, Joe, Larry Howard, and Bill Schelker. An Introduction to Structural Models. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada268151.

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Fair, Ray. VAR Models as Structural Approximations. National Bureau of Economic Research, 1988. http://dx.doi.org/10.3386/w2495.

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Galiani, Sebastian, and Juan Pantano. Structural Models: Inception and Frontier. National Bureau of Economic Research, 2021. http://dx.doi.org/10.3386/w28698.

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Kuether, Robert J., Jonel Ortiz, and Mark Chen. Model Order Reduction of Nonviscously Damped Structural Dynamic Models. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1475503.

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Koşar, Gizem, and Cormac O'Dea. Expectations Data in Structural Microeconomic Models. National Bureau of Economic Research, 2022. http://dx.doi.org/10.3386/w30094.

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Attansio, Orazio, and Debbie Blair. Structural modelling in policymaking. Centre for Excellence and Development Impact and Learning (CEDIL), 2018. http://dx.doi.org/10.51744/cip9.

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Structural modelling, that is the use of behavioural models to add a framework to the decision problem of an agent, is a useful yet underused tool in evaluation. This paper provides a general introduction to structural modelling, as well as an overview of other commonly used evaluation techniques in Economics and other social sciences. It then goes on to show with three key case studies, how structural models can be used to enrich the findings from randomised control trials. The case studies cover a wide range of policy questions: examining demand for health products in Kenya, incentivising te

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HAMMERAND, DANIEL C., SAMUEL W. KEY, J. T. ODEN, et al. Structural Simulations Using Multi-Resolution Material Models. Office of Scientific and Technical Information (OSTI), 2001. http://dx.doi.org/10.2172/789595.

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Chen, Le-Yu. Identification of structural dynamic discrete choice models. Institute for Fiscal Studies, 2009. http://dx.doi.org/10.1920/wp.cem.2009.0809.

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Weijters, Bert. Analyzing Experimental Data in Structural Equation Models. Instats Inc., 2023. http://dx.doi.org/10.61700/zclk0a8vgkfaa706.

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This two-day workshop, 'Analyzing Experimental Data using Structural Equation Modeling', led by Bert Weijters from Ghent University, provides a comprehensive understanding of SEM and its applications in research, with a focus on using Mplus software for SEM analysis. Ideal for PhD students, professors, and professional researchers in Psychology, Education, Management, and Marketing, the seminar offers practical experience in data analysis and an official Instats certificate of completion, with ECTS Equivalent points for European students.

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Romero-Chamorro, José Vicente, and Sara Naranjo-Saldarriaga. Weather Shocks and Inflation Expectations in Semi-Structural Models. Banco de la República Colombia, 2022. http://dx.doi.org/10.32468/be.1218.

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Colombia is particularly affected by the El Niño Southern Oscillation (ENSO) weather fluctuations. In this context, this study explores how the adverse weather events linked to ENSO affect the inflation expectations in Colombia and how to incorporate these second-round effects into a small open economy New Keynesian model. Using BVARx models we provide evidence that the inflation expectations obtained from surveys and break-even inflation measures are affected by weather supply shocks. Later, using this stylised fact, we modify one of the core forecasting models of the Banco de la República by

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