Data/hora: 28/05/2024 17:03:31

Provedor de dados: | 31
País: | United States
Título: | A Mata Geweke–Hajivassiliou–Keane multivariate normal simulator
Autores: | Gates,   Richard.
Data: | 2011-11-04
Ano: | 2006
Palavras-chave: | GHK; Maximum simulated likelihood; Monte Carlo; Quasi–Monte Carlo; Importance sampling; Number-theoretic statistics; Research Methods/ Statistical Methods.
Resumo: | 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
Idioma: | Inglês

Identificador:

st0102

http://purl.umn.edu/117569

Relação: | Stata Journal&gt;Volume 6, Number 2, 2nd Quarter 2006
Formato: | 24