Random Sampling Distributions.

Perfectly random sampling of truncated multinormal distributions

A “coupling from the past” construction of the Gibbs sampler process is used to perfectly simulate a random vector in a box B, a Cartesian product of bounded intervals. An algorithm to sample vectors with multinormal distribution truncated to B is implemented. AMS Classification 60G15 60G10 65C05

Random Distributions, Random Affine Systems, Sampling of Renewal Processes

Sampling Distributions Sampling Distributions

Ordered Random Variables from Discontinuous Distributions

In the absolutely continuous case, order statistics, record values and several other models of ordered random variables can be viewed as special cases of generalized order statistics, which enables a unified treatment of their theory. This paper deals with discontinuous generalized order statistics, continuing on the recent work of Tran (2006). Specifically, we show that in general neither re...

Sampling and Sampling Distributions

A sample is a group of objects or readings taken from a population for counting or measurement. We shall distinguish between two kinds of populations — finite populations and infinite populations. The sample must be random, meaning that all possible samples of a particular size must have equal probabilities of being chosen from the population. This will prevent bias in the sampling process. Mos...