Sequential Monte Carlo EM for multivariate probit models [PDF]
Computational Statistics & Data Analysis, 2013 Multivariate probit models (MPM) have the appealing feature of capturing some of the dependence structure between the components of multidimensional binary responses. The key for the dependence modelling is the covariance matrix of an underlying latent multivariate Gaussian.
Giusi Moffa, Jack Kuipers
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Parameter Estimation in Probit Model for Multivariate Multinomial Response Using SMLE
Jurnal Eksakta, 2011 In the research field of transportation, market research and politics, often involving the response of the multinomial multivariate observations. In this paper, we discused a modeling of multivariate multinomial responses using probit model. The estimated parameters were calculated using Maximum Likelihood Estimations (
Jaka Nugraha
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Likelihood Analysis of Multivariate Probit Models Using a Parameter Expanded MCEM Algorithm [PDF]
Technometrics, 2010 Multivariate binary data arise in a variety of settings. In this paper, we propose a practical and efficient computational framework for maximum likelihood estimation of multivariate probit regression models. This approach uses the Monte Carlo EM (MCEM) algorithm, with parameter expansion to complete the M-step, to avoid the direct evaluation of the ...
Huiping Xu, Bruce Α. Craig
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Data Augmentation in the Bayesian Multivariate Probit Model [PDF]
, 2004 This paper is concerned with the Bayesian estimation of a Multivariate Probit model. In particular, this paper provides an algorithm that obtains draws with low correlation much faster than a pure Gibbs sampling algorithm.
León-González, R.
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Development of Multivariate Ordered Probit Model to Understand Household Vehicle Ownership Behavior in Xiaoshan District of Hangzhou, China [PDF]
Sustainability, 2018 With the rapid increase of motorization in China, transitions have taken place in regards to traditional private transportation modes. This paper aims to understand four types of vehicle ownership within a household, including automobile, motorcycle ...
Jie Ma, Xin Ye, Cheng Shi
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Estimation of Multivariate Probit Models via Bivariate Probit
, 2015 John Mullahy
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Bayesian Analysis of Multivariate Longitudinal Ordinal Data Using Multiple Multivariate Probit Models [PDF]
American Journal of Theoretical and Applied Statistics, 2023 Xiao Zhang
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Sampling the Variance-Covariance Matrix in the Bayesian Multivariate Probit Model [PDF]
, 2003 This paper is concerned with the Bayesian estimation of a Multivariate Probit model. In particular, this paper provides a method to sample the restricted variancecovariance matrix directly from its conditional posterior density.
Leon-Gonzalez, R.
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Estimation of multivariate probit models by exact maximum likelihood [PDF]
, 2009 In this paper, we develop a new numerical method to estimate a multivariate probit model. To this end, we derive a new decomposition of normal multivariate integrals that has two appealing properties. First, the decomposition may be written as the sum of
Alberto Holly +2 more
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A limited information estimator for the multivariate ordinal probit model
Applied Economics, 2000 A limited information estimator for the multivariate ordinal probit model is developed. The main advantage of the estimator is that even for high dimensional models, the estimation procedure requires the evaluation of bivariate normal integrals only. The proposed estimator also avoids the potential problem of encountering local maxima in the estimation
Tsu‐Tan Fu +3 more
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