The toolbox includes:
1. fast random number generators from the truncated univariate and multivariate student/normal distributions;
2. (Quasi-) Monte Carlo estimator of the cumulative distribution function of the multivariate student/normal;
3. 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, Volume 79, Part 1, pp. 1-24
Zdravko Botev (2022). Truncated Normal and Student's t-distribution toolbox (https://www.mathworks.com/matlabcentral/fileexchange/53796-truncated-normal-and-student-s-t-distribution-toolbox), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
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