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	Provedor de dados AgEcon (2) Autor Cappellari, Lorenzo (1) Gates, Richard (1) Jenkins, Stephen P. (1) Palavra-chave GHK (2) Research Methods/ Statistical Methods (2) Importance sampling (1) Maximum likelihood estimation (1) Maximum simulated likelihood (1) Monte Carlo (1) Multivariate probit regression model (1) Mvppred (1) Mvprobit (1) Number-theoretic statistics (1) Quasi–Monte Carlo (1) Mais... Tipo do documento Journal Article (2) Ano 2006 (1) 2003 (1) País United States (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Multivariate probit regression using simulated maximum likelihood AgEcon Cappellari, Lorenzo; Jenkins, Stephen P.. We discuss the application of the GHK simulation method for maximum likelihood estimation of the multivariate probit regression model and describe and illustrate a Stata program mvprobit for this purpose. Tipo: Journal Article Palavras-chave: Maximum likelihood estimation; Multivariate probit regression model; GHK; Mvprobit; Mvppred; Research Methods/ Statistical Methods. Ano: 2003 URL: http://purl.umn.edu/116115 A Mata Geweke–Hajivassiliou–Keane multivariate normal simulator AgEcon Gates, Richard. An accurate and efficient numerical approximation of the multivariate normal (MVN) distribution function is necessary for obtaining maximum likelihood estimates for models involving the MVN distribution. Numerical integration through simulation (Monte Carlo) or number-theoretic (quasi–Monte Carlo) techniques is one way to accomplish this task. One popular simulation technique is the Geweke–Hajivassiliou–Keane MVN simulator. This paper reviews this technique and introduces a Mata function that implements it. It also computes analytical first-order derivatives of the simulated probability with respect to the variables and the variance–covariance parameters. Tipo: Journal Article Palavras-chave: GHK; Maximum simulated likelihood; Monte Carlo; Quasi–Monte Carlo; Importance sampling; Number-theoretic statistics; Research Methods/ Statistical Methods. Ano: 2006 URL: http://purl.umn.edu/117569 Registros recuperados: 2 Primeira ... 1 ... Última

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