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 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 Multinomial Probit Model Estimation Revisited written by and published by . This book was released on 1989 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Maximum Likelihood for the Multinomial Probit Model written by Nicholas M. Kiefer and published by . This book was released on 1995 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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 Estimation in Models for Multinomial Response Data written by Ranjini Natarajan and published by . This book was released on 1995 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Logit and Probit written by Vani K. Borooah and published by SAGE. This book was released on 2002 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many problems in the social sciences are amenable to analysis using the analytical tools of logit and probit models. This book explains what ordered and multinomial models are and also shows how to apply them to analysing issues in the social sciences.
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 Linear Probability Logit and Probit Models written by John H. Aldrich and published by SAGE. This book was released on 1984-11 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: After showing why ordinary regression analysis is not appropriate for investigating dichotomous or otherwise 'limited' dependent variables, this volume examines three techniques which are well suited for such data. It reviews the linear probability model and discusses alternative specifications of non-linear models.
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.
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 A Bayesian Multinomial Probit Model for the Analysis of Panel Choice Data written by Duncan K. H. Fong and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new Bayesian multinomial probit model is proposed for the analysis of panel choice data. Using a parameter expansion technique, we are able to devise a Markov Chain Monte Carlo algorithm to compute our Bayesian estimates efficiently. We also show that the proposed procedure enables the estimation of individual level coefficients for the single-period multinomial probit model even when the available prior information is vague. We apply our new procedure to consumer purchase data and reanalyze a well-known scanner panel dataset that reveals new substantive insights. In addition, we delineate a number of advantageous features of our proposed procedure over several benchmark models. Finally, through a simulation analysis employing a fractional factorial design, we demonstrate that the results from our proposed model are quite robust with respect to differing factors across various conditions.
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 Multinomial Probit Estimation of Models Exhibiting a General Error Covariance Structure Without Nuisance Parameters written by Breslaw, Jon A and published by . This book was released on 1993 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:
