This paper describes the Bayesian approach for reliability demonstration test based on the samples from a finite population. The Bayesian approach involves the technical method about how to combine the prior distribution and the likelihood function to pro

We want to accept or reject a finite population with reliability demonstration test. In this paper, we will describe Bayesian approaches for the reliability demonstration test based on the samples from a finite population. The Bayesian method is an approach that prior distribution and likelihood function combine to from posterior distribution. When we select somethings in a samples, we consider hypergeometric distribution. In this paper, we will explain the conjugacy of the beta-binomial distribution and hypergeometric distribution. The purpose of this paper is to make a decision between accept and reject in a finite population based on the conjugacy of the beta-binomial distribution.

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application.

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application.

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.