Calculation of multivariate normal probabilities by simulation, with applications to maximum simulated likelihood estimation
Lorenzo Cappellari
Catholic University of Milan
Milan, Italy
and University of Essex
Colchester, UK
[email protected]
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Stephen P. Jenkins
University of Essex
Colchester, UK
[email protected]
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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 themselves. Several illustrations show how
the programs may be used for maximum simulated likelihood estimation.
View all articles by these authors:
Lorenzo Cappellari, Stephen P. Jenkins
View all articles with these keywords:
mdraws, egen function mvnp(), simulation estimation, maximum simulated likelihood, multivariate probit, Halton sequences, pseudorandom sequences, multivariate normal, GHK simulator
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