Calculation of multivariate normal probabilities by simulation, with applications to maximum simulated likelihood estimation

Lorenzo Cappellari and Stephen Jenkins ()

Stata Journal, 2006, vol. 6, issue 2, pages 156-189

Abstract: We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata programs for this purpose: mdraws for deriving draws from the standard uniform density using either Halton or pseudorandom sequences, and an egen function, mvnp(), for calculating the probabilities them- selves. Several illustrations show how the programs may be used for maximum simulated likelihood estimation. Copyright 2006 by StataCorp LP.

Keywords: mdraws; egen function mvnp( ); simulation estimation; maxi- mum simulated likelihood; multivariate probit; Halton sequences; pseudorandom sequences; multivariate normal; GHK simulator (search for similar items in EconPapers)
Date: 2006
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Related works:
Working Paper: Calculation of Multivariate Normal Probabilities by Simulation, with Applications to Maximum Simulated Likelihood Estimation (2006)
Working Paper: Calculation of Multivariate Normal Probabilities by Simulation, with Applications to Maximum Simulated Likelihood Estimation (2006)
Working Paper: Calculation of Multivariate Normal Probabilities by Simulation, with Applications to Maximum Simulated Likelihood Estimation (2006)
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Persistent link: http://EconPapers.repec.org/RePEc:tsj:stataj:v:6:y:2006:i:2:p:156-189

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