Truncated Normal Distribution Toolbox
The 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.
package
Author(s)
Leo Belzile and Z. I. Botev, email: botev@unsw.edu.au and web page: https://web.maths.unsw.edu.au/~zdravkobotev/
References
- 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