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Author: Carlos Daganzo
Publisher: Elsevier
ISBN: 1483299341
Category : Business & Economics
Languages : en
Pages : 239
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Book Description
Multinomial Probit
Author: Carlos Daganzo
Publisher: Elsevier
ISBN: 1483299341
Category : Business & Economics
Languages : en
Pages : 239
Get Book Here
Book Description
Multinomial Probit
Author: Yosef Sheffi
Publisher:
ISBN:
Category : Probits
Languages : en
Pages : 28
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Book Description
Author: Wagner A. Kamakura
Publisher:
ISBN:
Category :
Languages : en
Pages : 13
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Book Description
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.
Author:
Publisher:
ISBN:
Category : Automobile ownership
Languages : en
Pages : 56
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Book Description
Author: Vani K. Borooah
Publisher: SAGE
ISBN: 9780761922421
Category : Mathematics
Languages : en
Pages : 108
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Book Description
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.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 15
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Book Description
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.
Author: Nicholas M. Kiefer
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 48
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Book Description
Author: Roman Liesenfeld
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
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]
Author: Carlos Daganzo
Publisher:
ISBN:
Category : Probits
Languages : en
Pages : 50
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Book Description
Author: John H. Aldrich
Publisher: SAGE
ISBN: 9780803921337
Category : Mathematics
Languages : en
Pages : 100
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Book Description
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.
