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
We study the performance of alternative sampling methods for estimating multivariate normal probabil...
When a distribution such as the multivariate normal is assumed to hold for a population, estimates o...
This is the R code for the simulation-based results related to the paper "Bounds for the normal appr...
We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata...
We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata...
An accurate and efficient numerical approximation of the multivariate normal (MVN) distribution func...
A major stumbling block in multivariate discrete data analysis is the problem of evaluating the outc...
The role of Multivariate Normal Probabilities in Econometric Models has in the past been somewhat re...
This paper discusses the increasing importance of probability simulation methods in the context of M...
We apply a new simulation method that solves the multidimensional probability integrals that arise i...
We study the performance of alternative sampling methods for estimating multivariate normal probabil...
Miwa et al. (2003) proposed a numerical algo-rithm for evaluating multivariate normal probabil-ities...
This 1992 paper appeared in 1995 in Statistics and Computing and the gist of it is contained in Mont...
Miwa et al. (2003) proposed a numerical algorithm for evaluating multivariate normal probabilities. ...
ghk2() estimates cumulative multivariate normal probabilities and optionally computes scores. It is ...
We study the performance of alternative sampling methods for estimating multivariate normal probabil...
When a distribution such as the multivariate normal is assumed to hold for a population, estimates o...
This is the R code for the simulation-based results related to the paper "Bounds for the normal appr...
We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata...
We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata...
An accurate and efficient numerical approximation of the multivariate normal (MVN) distribution func...
A major stumbling block in multivariate discrete data analysis is the problem of evaluating the outc...
The role of Multivariate Normal Probabilities in Econometric Models has in the past been somewhat re...
This paper discusses the increasing importance of probability simulation methods in the context of M...
We apply a new simulation method that solves the multidimensional probability integrals that arise i...
We study the performance of alternative sampling methods for estimating multivariate normal probabil...
Miwa et al. (2003) proposed a numerical algo-rithm for evaluating multivariate normal probabil-ities...
This 1992 paper appeared in 1995 in Statistics and Computing and the gist of it is contained in Mont...
Miwa et al. (2003) proposed a numerical algorithm for evaluating multivariate normal probabilities. ...
ghk2() estimates cumulative multivariate normal probabilities and optionally computes scores. It is ...
We study the performance of alternative sampling methods for estimating multivariate normal probabil...
When a distribution such as the multivariate normal is assumed to hold for a population, estimates o...
This is the R code for the simulation-based results related to the paper "Bounds for the normal appr...