TruncatedNormal-package.RdThe routines include:
generator of independent and identically distributed random vectors from the truncated univariate and multivariate distributions;
(Quasi-) Monte Carlo estimator and a deterministic upper bound of the cumulative distribution function of the multivariate normal and Student distributions;
algorithm for the accurate computation of the quantile function of the normal distribution in the extremes of its tails.
Z. I. Botev (2017), The Normal Law Under Linear Restrictions: Simulation and Estimation via Minimax Tilting, Journal of the Royal Statistical Society, Series B, 79 (1), pp. 1--24.
Z. I. Botev and P. L'Ecuyer (2015), Efficient Estimation and Simulation of the Truncated Multivariate Student-t Distribution, Proceedings of the 2015 Winter Simulation Conference, Huntington Beach, CA, USA
Gibson G. J., Glasbey C. A., Elston D. A. (1994), Monte Carlo evaluation of multivariate normal integrals and sensitivity to variate ordering, In: Advances in Numerical Methods and Applications, pages 120--126