An efficient decomposition of the expectation of the maximum for the multivariate normal and related distributions
多元正态及相关分布下最大值期望的高效分解
In structural dynamic discrete choice models, Monte Carlo integration has been the only way to evaluate the expectation of the maximum when errors are normally distributed. In this paper, however, I show that the expectation of the maximum can be decomposed as a linear combination of multivariate normal CDFs. For related distributions, such as the multivariate t-distribution, this expectation has a similar decomposition. My computational results show speed benefits of my…