Hierarchical Bayesian Method Study by Dong Xiaojing (23 results)
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Taschenbuch. Condition: Neu. Neuware - A major breakthrough in travel demand modeling in the early 1970's was modeling based on disaggregate (individual) level data (McFadden 2001). Although the disaggregate model focuses on individual level behavior, the estimated model parameters are fixed across individuals. To incorporate un…observed taste variations across individuals, recent developments allow for the parameters to vary across individuals, such as the Mixed Logit model, where the parameters are assumed to follow a distribution. The mixed logit model recognizes the differences among individuals, but it does not distinguish individuals who respond differently to travel service changes. This study focuses on the application of the Hierarchical Bayesian method to obtain individual level inferences. We demonstrate the advantage of this method by obtaining a more reasonable distribution of value of travel time relative to the distribution obtained from the mixed logit model. In addition, the HB method helps us to combine information from both revealed and stated preference data, where the revealed preference data is limited to properties of only the chosen alternatives.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Revision with unchanged content. A major breakthrough in travel demand modeling in the early 1970's was modeling based on disaggregate (individual) level data (McFadden 2001). Although the disaggregate model focuses on individual le…vel behavior, the estimated model parameters are fixed across individuals. To incorporate unobserved taste variations across individuals, recent developments allow for the parameters to vary across individuals, such as the Mixed Logit model, where the parameters are assumed to follow a distribution. The mixed logit model recognizes the differences among individuals, but it does not distinguish individuals who respond differently to travel service changes. This study focuses on the application of the Hierarchical Bayesian method to obtain individual level inferences. We demonstrate the advantage of this method by obtaining a more reasonable distribution of value of travel time relative to the distribution obtained from the mixed logit model. In addition, the HB method helps us to combine information from both revealed and stated preference data, where the revealed preference data is limited to properties of only the chosen alternatives. 68 pp. Englisch.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Dong Xiaojingis an Assistant Professor of Marketing at theLeavey School of Business, Santa Clara University.She got her PhD from Northwestern University(Evanston, IL) and MS degree atMIT (Cambridge, MA)….Revision with unchanged co.
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Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2007
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Condition: New. Print on Demand pp. 80 67:B&W 6.69 x 9.61 in or 244 x 170 mm (Pinched Crown) Perfect Bound on White w/Gloss Lam.
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Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2007
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Published by VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2007
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Revision with unchanged content. A major breakthrough in travel demand modeling in the early 1970's was modeling based on disaggregate (individual) level data (McFadden 2001). Although the disaggregate model focuses on individual level…behavior, the estimated model parameters are fixed across individuals. To incorporate unobserved taste variations across individuals, recent developments allow for the parameters to vary across individuals, such as the Mixed Logit model, where the parameters are assumed to follow a distribution. The mixed logit model recognizes the differences among individuals, but it does not distinguish individuals who respond differently to travel service changes. This study focuses on the application of the Hierarchical Bayesian method to obtain individual level inferences. We demonstrate the advantage of this method by obtaining a more reasonable distribution of value of travel time relative to the distribution obtained from the mixed logit model. In addition, the HB method helps us to combine information from both revealed and stated preference data, where the revealed preference data is limited to properties of only the chosen alternatives.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Revision with unchanged content. A major breakthrough in travel demand modeling in the early 1970's was modeling based on disaggregate (individual) level data (McFadden 2001). Although the disaggregate model focuses on individual level b…ehavior, the estimated model parameters are fixed across individuals. To incorporate unobserved taste variations across individuals, recent developments allow for the parameters to vary across individuals, such as the Mixed Logit model, where the parameters are assumed to follow a distribution. The mixed logit model recognizes the differences among individuals, but it does not distinguish individuals who respond differently to travel service changes. This study focuses on the application of the Hierarchical Bayesian method to obtain individual level inferences. We demonstrate the advantage of this method by obtaining a more reasonable distribution of value of travel time relative to the distribution obtained from the mixed logit model. In addition, the HB method helps us to combine information from both revealed and stated preference data, where the revealed preference data is limited to properties of only the chosen alternatives.
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Taschenbuch. Condition: Neu. Hierarchical Bayesian Method in the Study of Individual Level Behavior | In the Context of Discrete Choice Modeling with Revealed and Stated Preference Data | Xiaojing Dong | Taschenbuch | 68 S. | Englisch | 2012 | AV Akademikerverlag | EAN 9783639415056 | Verantwortliche Person für die EU: preigu Gm…bH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.
