Abstract
Laud et al. (1993) describe a method for random variate generation from D-distributions. In this paper an alternative method using substitution sampling is given. An algorithm for the random variate generation from SD-distributions is also given.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Devroye, L. (1986) Non-Uniform Random Variate Generation. Springer-Verlag, Berlin.
Gelfand, A. E. and Smith, A. F. M. (1990) Sampling-based approaches to calculating marginal densities. Journal of the American Statistical Association, 85, 398–409.
Laud, P. W. (1977) Bayesian nonparametric inference in reliability. Ph.D. Dissertation, University of Missouri, Columbia, MO.
Laud, P. W., Damien, P. and Smith, A. F. M. (1993) Random variate generation from D-distributions. Statistics and Computing, 3, 109–12.
Damien, P., Laud, P. W. and Smith, A. F. M. (1995) Random variate generation approximating infinitely divisible distributions with application to Bayesian inference. Journal of the Royal Statistical Society Series B. 57, 547–564.
Smith, A. F. M. and Roberts, G. O. (1993) Bayesian computation via the Gibbs sampler and related Markov chain Monte Carlo methods. Journal of the Royal Statistical Society Series B 55, 3–23.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Walker, S. Generating random variates from D-distributions via substitution sampling. Stat Comput 5, 311–315 (1995). https://doi.org/10.1007/BF00162504
Issue Date:
DOI: https://doi.org/10.1007/BF00162504