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Статті в журналах з теми "Integrated Choice and Latent Variable"
Chen, Jian, and Shoujie Li. "Mode Choice Model for Public Transport with Categorized Latent Variables." Mathematical Problems in Engineering 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/7861945.
Повний текст джерелаMahpour, Alireza, Amirreza Mamdoohi, Taha HosseinRashidi, Basil Schmid, and Kay W. Axhausen. "Shopping destination choice in Tehran: An integrated choice and latent variable approach." Transportation Research Part F: Traffic Psychology and Behaviour 58 (October 2018): 566–80. http://dx.doi.org/10.1016/j.trf.2018.06.045.
Повний текст джерелаPolitis, Ioannis, Panagiotis Papaioannou, and Socrates Basbas. "Integrated Choice and Latent Variable Models for evaluating Flexible Transport Mode choice." Research in Transportation Business & Management 3 (August 2012): 24–38. http://dx.doi.org/10.1016/j.rtbm.2012.06.007.
Повний текст джерелаSoto, Jose J., Luis Márquez, and Luis F. Macea. "Accounting for attitudes on parking choice: An integrated choice and latent variable approach." Transportation Research Part A: Policy and Practice 111 (May 2018): 65–77. http://dx.doi.org/10.1016/j.tra.2018.03.003.
Повний текст джерелаChen, Ching-Fu, Chiang Fu, and Pei-Ya Siao. "Exploring electric moped sharing preferences with integrated choice and latent variable approach." Transportation Research Part D: Transport and Environment 121 (August 2023): 103837. http://dx.doi.org/10.1016/j.trd.2023.103837.
Повний текст джерелаSohn, Keemin. "An Expectation-Maximization Algorithm to Estimate the Integrated Choice and Latent Variable Model." Transportation Science 51, no. 3 (August 2017): 946–67. http://dx.doi.org/10.1287/trsc.2016.0696.
Повний текст джерелаVij, Akshay, and Joan L. Walker. "How, when and why integrated choice and latent variable models are latently useful." Transportation Research Part B: Methodological 90 (August 2016): 192–217. http://dx.doi.org/10.1016/j.trb.2016.04.021.
Повний текст джерелаMohiuddin, Hossain, Md Musfiqur Rahman Bhuiya, Shaila Jamal, and Zhi Chen. "Exploring the Choice of Bicycling and Walking in Rajshahi, Bangladesh: An Application of Integrated Choice and Latent Variable (ICLV) Models." Sustainability 14, no. 22 (November 9, 2022): 14784. http://dx.doi.org/10.3390/su142214784.
Повний текст джерелаChae, Dasol, Jaeyoung Jung, and Keemin Sohn. "Facilitating an expectation-maximization (EM) algorithm to solve an integrated choice and latent variable (ICLV) model with fully correlated latent variables." Journal of Choice Modelling 26 (March 2018): 64–79. http://dx.doi.org/10.1016/j.jocm.2017.08.001.
Повний текст джерелаYeh, Ching-Hua, Monika Hartmann, Matthew Gorton, Barbara Tocco, Virginie Amilien, and Kamilla Knutsen Steinnes. "Looking behind the choice of organic: A cross-country analysis applying Integrated Choice and Latent Variable Models." Appetite 167 (December 2021): 105591. http://dx.doi.org/10.1016/j.appet.2021.105591.
Повний текст джерелаДисертації з теми "Integrated Choice and Latent Variable"
Walker, Joan Leslie. "Extended discrete choice models : integrated framework, flexible error structures, and latent variables." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/32704.
Повний текст джерелаIncludes bibliographical references (leaves 199-209).
Discrete choice methods model a decision-maker's choice among a set of mutually exclusive and collectively exhaustive alternatives. They are used in a variety of disciplines (transportation, economics, psychology, public policy, etc.) in order to inform policy and marketing decisions and to better understand and test hypotheses of behavior. This dissertation is concerned with the enhancement of discrete choice methods. The workhorses of discrete choice are the multinomial and nested logit models. These models rely on simplistic assumptions, and there has been much debate regarding their validity. Behavioral researchers have emphasized the importance of amorphous influences on behavior such as context, knowledge, and attitudes. Cognitive scientists have uncovered anomalies that appear to violate the microeconomic underpinnings that are the basis of discrete choice analysis. To address these criticisms, researchers have for some time been working on enhancing discrete choice models. While there have been numerous advances, typically these extensions are examined and applied in isolation. In this dissertation, we present, empirically demonstrate, and test a generalized methodological framework that integrates the extensions of discrete choice. The basic technique for integrating the methods is to start with the multinomial logit formulation, and then add extensions that relax simplifying assumptions and enrich the capabilities of the basic model. The extensions include: - Specifying factor analytic (probit-like) disturbances i order to provide a flexible covariance structure, thereby relaxing the IIA condition and enabling estimation of unobserved heterogeneity through techniques such as random parameters. - Combining revealed and stated preferences in order to draw on the advantages of both types of data, thereby reducing bias and improving efficiency of the parameter estimates. - Incorporating latent variables in order to provide a richer explanation of behavior by explicitly representing the formation and effects of latent constructs such as attitudes and perceptions. - Stipulating latent classes in order to capture latent segmentation, for example. in terms of taste parameters, choice sets, and decision protocols. The guiding philosophy is that the generalized framework allows for a more realistic representation of the behavior inherent in the choice process, and consequently a better understanding of behavior, improvements in forecasts, and valuable information regarding the validity of simpler model structures. These generalized models often result in functional forms composed of complex multidimensional integrals. Therefore a key aspect of the framework is its 'logit kernel' formulation in which the disturbance of the choice model includes an additive i.i.d Gumbel term. This formulation can replicate all known error structures (as we show here) and it leads to a straightforward probability simulator (of a multinomial logit form) for use in maximum simulated likelihood estimation. The proposed framework and suggested implementation leads to a flexible, tractable, theoretically grounded, empirically verifiable. and intuitive method for incorporating and integrating complex behavioral processes in the choice model. In addition to the generalized framework, contributions are also made to two of the key methodologies hat make up the framework. First, we present new results regarding identification and normalization of he disturbance parameters of a logit kernel model. n particular, we show that identification is not always intuitive, it is not always analogous to the systematic portion. and it is not necessarily like probit. Second. we present a general framework and methodology for incorporating latent variables into choice models via the integration of choice and latent variable models and the use of psychometric data (for example. responses to attitudinal survey questions). Throughout the dissertation, empirical results are presented to highlight findings and to empirically demonstrate and test the generalized framework. The impact of the extensions cannot be known a priori. and the only way to test their value (as well as the validity of a simpler model structure) is to estimate the complex models. Sometimes the extensions result in large improvements in fit as well as in more satisfying behavioral representations. Conversely, sometimes the extensions have marginal impact. thereby showing that the more parsimonious structures are robust. All methods are often not necessary. and the generalized framework provides an approach for developing the best model specification that makes use of available data and is reflective of behavioral hypotheses.
by Joan Leslie Walker.
Ph.D.
Bouscasse, Hélène. "Essays on travel mode choice modeling : a discrete choice approach of the interactions between economic and behavioral theories." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE2106/document.
Повний текст джерелаThe objective of this thesis is to incorporate aspects of psychology and behavioral economics theories in discrete choice models to promote a better understanding of mode choice at regional level. Part II examines the inclusion of latent variables to explain mode choice. A literature review of integrated choice and latent variable models – that is, models combining a structural equation model and a discrete choice model – is followed by the estimation of an integrated choice and latent variable model to show how the heterogeneity of economic outputs (here, value of time) can be explained with latent variables (here, perceived comfort in public transport) and observable variables (here, the guarantee of a seat). The simulation of scenarios shows, however, that the economic gain (decrease in value of time) is higher when policies address tangible factors than when they address latent factors. On the basis of a mediation model, the estimation of a structural equation model furthermore implies that the influence of environmental concern on mode choice habits is partially mediated by the indirect utility derived frompublic transport use. Part III examines two utility formulations taken from behavioral economics: 1) rankdependent utility to model risky choices, and 2) reference-dependent utility. Firstly, a rank-dependent utility model is included in discrete choice models and, in particular, a latent-class model, in order to analyze intra- and inter-individual heterogeneity when the travel time is subject to variability. The results show that the probability of a delay is over-estimated for train travel and under-estimated for car travel, especially for car users, as train users are more likely to take into account the expected travel time. In the models that account for risk aversion, the utility functions are convex, which implies a decrease in value of time. Secondly, a new family of discrete choice models generalizing the multinomial logit model, the reference models, is estimated. On my data, these models allow for a better selection of explanatory variables than the multinomial logit model and a more robust estimation of economic outputs, particularly in cases of high unobserved heterogeneity. The economic formulation of reference models shows thatthe best empirical models are also more compatible with Tversky et Kahneman’s reference-dependent model
Lawson, Jordan L. "Strengthening Causal Inferences: Examining Instrument-Free Approaches to Addressing Endogeneity Bias in the Evaluation of an Integrated Student Support Program." Thesis, Boston College, 2019. http://hdl.handle.net/2345/bc-ir:108595.
Повний текст джерелаEducation researchers are frequently interested in examining the causal impact of academic services and interventions; however, it is often not feasible to randomly assign study elements to treatment conditions in the field of education (Adelson, 2013). When assignment to treatment conditions is non-random, the omission of any variables relevant to treatment selection creates a correlation between the treatment variable and the error in regression models. This is termed endogeneity (Ebbes, 2004). In the presence of endogeneity, treatment effect estimates from traditionally used regression approaches may be biased. The purpose of this study was to investigate the causal impact of an integrated student support model, namely City Connects, on student academic achievement. Given that students are not randomly assigned to the City Connects intervention, endogeneity bias may be present. To address this issue, two novel and underused statistical approaches were used with school admissions lottery data, namely Gaussian copula regression developed by Park and Gupta (2012), and Latent Instrumental Variable (LIV) regression developed by Peter Ebbes (2004). The use of real-world school admissions lottery data allowed the first-ever comparison of the two proposed methods with Instrumental Variable (IV) regression under a large-scale randomized control (RCT) trial. Additionally, the researcher used simulation data to investigate both the performance and boundaries of the two proposed methods compared with that of OLS and IV regression. Simulation study findings suggest that both Gaussian copula and LIV regression are useful approaches for addressing endogeneity bias across a range of research conditions. Furthermore, simulation findings suggest that the two proposed methods have important differences in their set of identifying assumptions, and that some assumptions are more crucial than others. Results from the application of the Gaussian copula and LIV regression in the City Connects school lottery admissions study demonstrated that receiving the City Connects model of integrated student support during elementary school has a positive impact on mathematics achievement. Such findings underscore the importance of addressing out-of-school barriers to learning
Thesis (PhD) — Boston College, 2019
Submitted to: Boston College. Lynch School of Education
Discipline: Educational Research, Measurement and Evaluation
Chaudhary, Ankita. "Impact of range anxiety on driver route choices using a panel-integrated choice latent variable model." Thesis, 2014. http://hdl.handle.net/2152/28254.
Повний текст джерелаtext
Biswas, Mehek. "An Integrated Choice and Latent Variable Framework to Incorporate the Influence of Travel Time Variability on Truck Route Choice." Thesis, 2018. https://etd.iisc.ac.in/handle/2005/4735.
Повний текст джерелаLai, Hzu-hao, and 賴思豪. "Modeling the Choice Behaviors of Freeway Electronic Toll Collection with an Integrated Choice and Latent Variables Approach." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/34846367174406603624.
Повний текст джерелаWan-PeiHu and 胡琬珮. "Latent Variable Choice Models Considering Heterogeneity, Correlation, and Endogeneity." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/05768734120036738214.
Повний текст джерела國立成功大學
交通管理學系碩博士班
96
In the past, the way that the discrete choice models treated the unobservable variables such as perceived and attitude variables caused some problems. For example, the estimated parameters were not consistent and efficient, the index could not be used directly to affect the policies, and the index may not be suitable in the prediction, and the unobservable variables are unchangeable as individuals vary. It results in some disadvantages for policies analysis and applications. Now the most widely used models is Maximum Simulated Likelihood to overcome the model with multi dimension parameter integration problems. There exists unstable situation in parameter calibrating as the number of simulated draws is not enough. The earlier reference seldom explored the influence of the model calibrating by simulating the number of draws. The number of draws is quite important. The purpose of this research is to use the simultaneous equations concepts for integrating latent variables and individual choice models, and decide the best number of the random draws. The parameters estimation will be more consistent, efficient, and stable. In addition, this study also discusses the heterogeneity, correlation, and hierarchy cause-and-effect of service quality perceived variables to increase the explanatory power in the models and to know the travelers’ riding behaviors. It will be implementing to policy analysis, to understand every policy variables on direct and indirect effect of choice behaviors, and to solve the problem which came about in the previous researches. The scope of this research was the intercity bus travelers of Taipei-Kaohsiung route in Taiwan. For the part of dealing with the latent variable choice models, the evidence shows that as the service satisfaction factors add in the model, the explanatory power will be improved. It also presented the methodology is efficient. For the part of the number of random draws, simulating the log-likelihood function of different latent variable choice models will boost as the simulating number increase. While the Halton random number reached to 4000, the improvement of the simulation to simulating the log-likelihood function was getting smooth. So this research picks 4,000 as the number of random draws. In this paper, if the latent variables are assumed as exogenous variables, the I II - - integrating latent variables heterogeneity and correlation of the choice model has better explanatory power. It presents that there are individual heterogeneity and correlation among the three service quality variables-convenience, commoditization and entertainment, the passengers’ interaction. In addition, there is positive influence on the travelers’ choices to the intercity bus companies by these three service quality satisfaction variables. The convenience and commoditization and entertainment satisfaction of the travelers to the bus companies will influence positively on travelers’ choice behaviors, and the convenience satisfaction is stronger than commoditization and entertainment satisfaction. Moreover, the travelers’ interaction satisfaction influence indirectly on the travelers’ choice behaviors to the bus companies through the convenience and commoditization and entertainment satisfaction of the travelers.
Yun-JuLin and 林韻如. "Consumer Preferences for Purchasing Electric Vehicles-An Application of Latent Variable Choice Model." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/93289658802899284704.
Повний текст джерелаDrill, Esther. "Statistical Methods for Integrated Cancer Genomic Data Using a Joint Latent Variable Model." Thesis, 2018. https://doi.org/10.7916/D85M7P7V.
Повний текст джерелаКниги з теми "Integrated Choice and Latent Variable"
Statistical Methods for Integrated Cancer Genomic Data Using a Joint Latent Variable Model. [New York, N.Y.?]: [publisher not identified], 2018.
Знайти повний текст джерелаЧастини книг з теми "Integrated Choice and Latent Variable"
Levin-Schwartz, Yuri, Vince D. Calhoun, and Tülay Adalı. "Multivariate Fusion of EEG and Functional MRI Data Using ICA: Algorithm Choice and Performance Analysis." In Latent Variable Analysis and Signal Separation, 489–96. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22482-4_57.
Повний текст джерелаHernandez-Garcia, Miguel R., and Sami F. Masri. "Multivariate Statistical Analysis for Detection and Identification of Faulty Sensors Using Latent Variable Methods." In Emboding Intelligence in Structures and Integrated Systems, 501–7. Stafa: Trans Tech Publications Ltd., 2008. http://dx.doi.org/10.4028/3-908158-13-3.501.
Повний текст джерелаPrato, Carlo G. "Data Analysis: Integrated Choice and Latent Variable Models." In International Encyclopedia of Transportation, 102–6. Elsevier, 2021. http://dx.doi.org/10.1016/b978-0-08-102671-7.10667-0.
Повний текст джерелаIlahi, Anugrah, Prawira F. Belgiawan, and Kay W. Axhausen. "Influence of pricing on mode choice decision integrated with latent variable." In Mapping the Travel Behavior Genome, 125–43. Elsevier, 2020. http://dx.doi.org/10.1016/b978-0-12-817340-4.00008-5.
Повний текст джерелаKitrinou, Eleni, Amalia Polydoropoulou, and Denis Bolduc. "Development of Integrated Choice and Latent Variable (ICLV) Models for the Residential Relocation Decision in Island Areas." In Choice Modelling: The State-of-the-art and The State-of-practice, 593–618. Emerald Group Publishing Limited, 2010. http://dx.doi.org/10.1108/9781849507738-027.
Повний текст джерелаTsirimpa, Athena, and Amalia Polydoropoulou. "The Impact of Traffic Information Acquisition on the Traffic Conditions of the Athens Greater Area." In Transportation Systems and Engineering, 174–91. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8473-7.ch009.
Повний текст джерелаBen-Akiva, Moshe, Joan Walker, Adriana T. Bernardino, Dinesh A. Gopinath, Taka Morikawa, and Amalia Polydoropoulou. "Integration of Choice and Latent Variable Models." In In Perpetual Motion, 431–70. Elsevier, 2002. http://dx.doi.org/10.1016/b978-008044044-6/50022-x.
Повний текст джерелаGuevara, Cristian Angelo, and Moshe Ben-Akiva. "Addressing Endogeneity in Discrete Choice Models: Assessing Control-Function and Latent-Variable Methods." In Choice Modelling: The State-of-the-art and The State-of-practice, 353–70. Emerald Group Publishing Limited, 2010. http://dx.doi.org/10.1108/9781849507738-016.
Повний текст джерелаEmmerink, Richard H. M., Peter Nijkamp, Piet Rietveld, and Jos N. Van Ommeren. "Variable Message Signs and Radio Traffic Information: An Integrated Empirical Analysis of Drivers’ Route Choice Behaviour." In Location, Travel and Information Technology, 343–61. Edward Elgar Publishing, 2004. http://dx.doi.org/10.4337/9781035304929.00026.
Повний текст джерелаNounou, Mohamed N., Hazem N. Nounou, and Muddu Madakyaru. "Multiscale Filtering and Applications to Chemical and Biological Systems." In Handbook of Research on Novel Soft Computing Intelligent Algorithms, 749–86. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-4450-2.ch025.
Повний текст джерелаТези доповідей конференцій з теми "Integrated Choice and Latent Variable"
Wassenaar, Henk Jan, Wei Chen, Jie Cheng, and Agus Sudjianto. "An Integrated Latent Variable Choice Modeling Approach for Enhancing Product Demand Modeling." In ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASME, 2004. http://dx.doi.org/10.1115/detc2004-57487.
Повний текст джерелаGhosh, Dipanjan D., Andrew Olewnik, and Kemper E. Lewis. "An Integrated Framework for Predicting Consumer Choice Through Modeling of Preference and Product Use Data." In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-68010.
Повний текст джерелаYang, Chen, Wei Wang, Zhibin Li, and Jian Lu. "Travel Mode Choice Based on Latent Variable Enriched Discrete Choice Model." In Second International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/41039(345)720.
Повний текст джерелаSalah, Aghiles, and Hady W. Lauw. "A Bayesian Latent Variable Model of User Preferences with Item Context." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/370.
Повний текст джерелаZhang, Rong, Jiaqi Shen, and Hao Liu. "Quantitative Analysis of Latent Variable and Its Integration with Freight Mode Choice Behavior Model." In 22nd COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2022. http://dx.doi.org/10.1061/9780784484265.257.
Повний текст джерелаMadakyaru, Muddu, Mohamed N. Nounou, and Hazem N. Nounou. "Enhanced modeling of distillation columns using integrated multiscale latent variable regression." In 2013 IEEE Symposium on Computational Intelligence in Control and Automation (CICA). IEEE, 2013. http://dx.doi.org/10.1109/cica.2013.6611666.
Повний текст джерелаLi, Xiufeng, Xiang Liu, Ning Wang, Decun Dong, and Wenjian Zhang. "Investigating the Key Factors Influencing Travelers’ Carsharing Choice – An Inclusion of Latent Variable Nested Logit Model." In 2019 IEEE Intelligent Transportation Systems Conference - ITSC. IEEE, 2019. http://dx.doi.org/10.1109/itsc.2019.8916949.
Повний текст джерелаLuo, Yin-Jyun, Sebastian Ewert, and Simon Dixon. "Towards Robust Unsupervised Disentanglement of Sequential Data — A Case Study Using Music Audio." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/458.
Повний текст джерелаYannou, Bernard, Jiliang Wang, Ndrianarilala Rianantsoa, Chris Hoyle, Mark Drayer, Wei Chen, Fabrice Alizon, and Jean-Pierre Mathieu. "Usage Coverage Model for Choice Modeling: Principles." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-87534.
Повний текст джерелаRoy, Rajkumar, Ian C. Parmee, and Graham Purchase. "Qualitative Evaluation of Engineering Designs Using Fuzzy Logic." In ASME 1996 Design Engineering Technical Conferences and Computers in Engineering Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-detc/dac-1449.
Повний текст джерела