Truncated multivariate Normal and Student distributions
A collection of functions to deal with the truncated univariate and multivariate normal and Student distributions, described in Botev (2017) and Botev and L’Ecuyer (2015).
Main features are
- simulation from multivariate truncated Normal and student distributions using an accept-reject algorithm based on minimax exponential tilting.
- (quasi) Monte-Carlo estimation of the distribution function using separation-of-variables together with exponential tilting for provable performances and theoretical upper bound on the error.
- Cholesky decomposition using the reordering algorithm of Gibson, Glasbey and Elston (1994).
To install the latest version from CRAN, use
install.packages("TruncatedNormal")
or else install the latest development from Github via
devtools::install_github("lbelzile/TruncatedNormal")
