Two practical procedures for estimating multivariate nonnormal probability density functions

This article presents two procedures for empirically estimating nonnormal joint probability density functions (pdf’s) that are operational with small samples. One procedure empirically estimates marginal distributions. Estimated marginal distributions are then used to transform variates to univariate normality; the transformed variates are assumed to have a multivariate normal distribution. The second approach exploits the identity that a joint distribution is the product of a conditional pdf and a marginal pdf. Conditional and marginal pdfs are individually estimated with this approach. Statistical tests for multivariate normality are also reviewed. © 1990 American Agricultural Economics Association.

Duke Scholars

Author Curtis R. Taylor Economics