Download or read book Multinomial Probit Model Estimation Revisited written by David S. Bunch and published by . This book was released on 1989 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Multinomial Probit Model Revisited written by Melvyn Weekes and published by . This book was released on 1993 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multinomial Probit Model Estimation written by and published by . This book was released on 1991 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: The multinomial probit (MNP) model offers a rather general and flexible framework for the analysis of discrete choices obtained from panel data and the specification of models with general error structures. However, this flexibility of specification has come at a relatively high price in terms of difficulty of computing maximum likelihood estimates ofthe model parameters and evaluating the associated choice function. This paper presents a new procedure for the estimation of MNP models, motivated primarily by the advances that have taken place in terms of computing environments and capabilities. the procedure derives its efficiency from execution in a parallel computing environment (CRAY YMP/8) and its accuracy from the use of better (but otherwise more computationally intensive) mathematical procedures. The paper also discusses and compares alternative nonlinear optimization procedures to search for the parameter values that maximize the likelihood function, in connection with Monte Carlo evaluation of the likelihood of each observation. The results are also compared to those obtained using the Clark approximation to evaluate the choice probabilities.
Download or read book On the Estimation of the Multinomial Probit Model written by Yosef Sheffi and published by . This book was released on 1980* with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multinomial Probit written by Carlos Daganzo and published by Elsevier. This book was released on 2014-06-28 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multinomial Probit
Download or read book The Estimation of Multinomial Probit Models written by Wagner A. Kamakura and published by . This book was released on 2014 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study proposes the estimation of Multinomial Probit models using Mendell-Elston's approximation to the cumulative multivariate normal for the computation of choice probabilities. The accuracy of this numerical approximation in computing probabilities is compared with other procedures used in existing calibration programs. Finally, the proposed estimation procedure is tested on simulated choice data.
Download or read book An Efficient Approach to Estimate and Predict with Multinomial Probit Models written by Carlos Daganzo and published by . This book was released on 1977 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Simulation Evaluation of Emerging Estimation Techniques for Multinomial Probit Models written by Priyadarshan Nandkumar Patil and published by . This book was released on 2016 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt: A simulation evaluation is presented to compare alternative estimation techniques for a five-alternative multinomial probit (MNP) model with random parameters, including cross-sectional and panel datasets and for scenarios with and without correlation among random parameters. The different estimation techniques assessed are: (1) The maximum approximate composite marginal likelihood (MACML) approach; (2) The Geweke-Hajivassiliou-Keane (GHK) simulator with Halton sequences, implemented in conjunction with the composite marginal likelihood (CML) estimation approach; (3) The GHK approach with sparse grid nodes and weights, implemented in conjunction with the composite marginal likelihood (CML) estimation approach; and (4) a Bayesian Markov Chain Monte Carlo (MCMC) approach. In addition, for comparison purposes, the GHK simulator with Halton sequences was implemented in conjunction with the traditional, full information maximum likelihood approach as well. The results indicate that the MACML approach provided the best performance in terms of the accuracy and precision of parameter recovery and estimation time for all data generation settings considered in this study. For panel data settings, the GHK approach with Halton sequences, when combined with the CML approach, provided better performance than when implemented with the full information maximum likelihood approach, albeit not better than the MACML approach. The sparse grid approach did not perform well in recovering the parameters as the dimension of integration increased, particularly so with the panel datasets. The Bayesian MCMC approach performed well in datasets without correlations among random parameters, but exhibited limitations in datasets with correlated parameters.
Download or read book Dynamic Invariant Multinomial Probit Model Identification Pretesting and Estimation written by Roman Liesenfeld and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "We present a new specification for the multinomial multiperiod Probit model with autocorrelated errors. In sharp contrast with commonly used specifications, ours is invariant with respect to the choice of a baseline alternative for utility differencing. It also nests these standard models as special cases, allowing for data based selection of the baseline alternatives for the latter. Likelihood evaluation is achieved under an Efficient Importance Sampling (EIS) version of the standard GHK algorithm. Several simulation experiments highlight identification, estimation and pretesting within the new class of multinomial multiperiod Probit models." [author's abstract]
Download or read book Panels for Transportation Planning written by Thomas F. Golob and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Panels for Transportation Planning argues that panels - repeated measurements on the same sets of households or individuals over time - can more effectively capture dynamic changes in travel behavior, and the factors which underlie these changes, than can conventional cross-sectional surveys. Because panels can collect information on household attributes, attitudes and perceptions, residential and employment choices, travel behavior and other variables - and then can collect information on changes in these variables over time - they help us to understand how and why people choose to travel as they do, and how and why these choices are likely to evolve in the future. This book is designed for a wide audience: survey researchers who seek information on methodological advancements and applications; transportation planners who want an improved understanding of dynamic changes in travel behavior; and instructors of graduate courses in urban and transportation planning, research methods, economics, sociology, and public policy. Each chapter has been prepared to stand alone to illustrate a particular theme or application. The book is divided into topical parts which address the most salient issues in the use of panels for transportation planning: panels as evaluation tools, regional planning applications, accounting for response bias, and modeling and forecasting issues. These parts describe panel applications in the US, Australia, Great Britain, Japan, and the Netherlands. Each chapter is supplemented by extensive references; more than 400 studies, reflecting the work of more than 700 authors, are cited in the text.
Download or read book Multinomial Probit Models with Factor based Autoregressive Errors a Computationally Efficient Estimation Approach written by Bolduc, Denis and published by Québec : Dép. d'économique, Université Laval. This book was released on 1991 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modeling Ordered Choices written by William H. Greene and published by Cambridge University Press. This book was released on 2010-04-08 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is increasingly common for analysts to seek out the opinions of individuals and organizations using attitudinal scales such as degree of satisfaction or importance attached to an issue. Examples include levels of obesity, seriousness of a health condition, attitudes towards service levels, opinions on products, voting intentions, and the degree of clarity of contracts. Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives. The methods have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance. This book brings together contributions in ordered choice modeling from a number of disciplines, synthesizing developments over the last fifty years, and suggests useful extensions to account for the wide range of sources of influence on choice.
Download or read book Conjoint Measurement written by Anders Gustafsson and published by Springer Science & Business Media. This book was released on 2007-09-12 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fascinating book covers all the recent developments in conjoint analysis. Leading scientists present different aspects of the theory and applications of this technique. A wide variety of models, techniques, and applications are discussed, including normative models that maximize return, extension of choice-based conjoint simulations, latent class, hierarchical Bayes modeling, new choice simulators, and normative models for representing competitive actions and reactions (based on game theory).
Download or read book Multinomial Probit Estimation of Models Exhibiting a General Error Convariance Structure Without Nuisance Parameters written by Jon A. Breslaw and published by . This book was released on 1993 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Cahier 9116 Multinomial Probit Models with Factor based Autoregressive Errors a Computationally Efficient Estimation Approach D Bolduc M Kaci written by Université Laval. Departement d'Economique. Faculté des Sciences Sociales and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Choice Modelling written by Stephane Hess and published by Edward Elgar Publishing. This book was released on 2024-06-05 with total page 797 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thoroughly revised second edition Handbook provides an authoritative and in-depth overview of choice modelling, covering essential topics range from data collection through model specification and estimation to analysis and use of results. It aptly emphasises the broad relevance of choice modelling when applied to a multitude of fields, including but not limited to transport, marketing, health and environmental economics.
Download or read book The Multinomial Multiperiod Probit Model written by Roman Liesenfeld and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we discuss parameter identification and likelihood evaluation for multinomial multiperiod Probit models. It is shown in particular that the standard autoregressive specification used in the literature can be interpreted as a latent common factor model. However, this specification is not invariant with respect to the selection of the baseline category. Hence, we propose an alternative specification which is invariant with respect to such a selection and identifies coefficients characterizing the stationary covariance matrix which are not identified in the standard approach. For likelihood evaluation requiring high-dimensional truncated integration we propose to use a generic procedure known as Efficient Importance Sampling (EIS). A special case of our proposed EIS algorithm is the standard GHK probability simulator. To illustrate the relative performance of both procedures we perform a set Monte-Carlo experiments. Our results indicate substantial numerical efficiency gains of the ML estimates based on GHK-EIS relative to ML estimates obtained by using GHK.
