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In this article, a model of single variable sampling plan with type I censoring is studied. Under the assumption that the variable is exponentially distributed and the loss function is a polynomial, an explicit expression of the Bayes risk is derived. Then, a simple and finite algorithm to determine an optimal sampling plan for minimizing the Bayes risk is suggested. Furthermore, a discretization method is proposed so that one can easily obtain an approximately optimal…

计量型一次抽样方案的贝叶斯方法AI 解读

In this paper, we develop a model of sampling plans for variables with a polynomial loss function, in which the decision function is either one-sided or two-sided. Based on a Bayesian approach, we suggest a simple finite algorithm for the determination of the optimal single sampling plan. Furthermore, for the case of a symmetric two-sided decision function, we propose an approximate method for determining its optimal single sampling plan.

计量型一次抽样方案的贝叶斯方法AI 解读

In this paper, we develop a model of sampling plans for variables with a polynomial loss function, in which the decision function is either one-sided or two-sided. Based on a Bayesian approach, we suggest a simple finite algorithm for the determination of the optimal single sampling plan. Furthermore, for the case of a symmetric two-sided decision function, we propose an approximate method for determining its optimal single sampling plan.

Sichel 复合泊松分布的推断AI 解读

In a long-tailed compound Poisson distribution introduced by Sichel, the probabilities can only readily be calculated if one of the parameters λ has half-integer values, that is, λ = m + 1/2, m integer. The maximum likelihood estimation of this parameter is compared with an approximate method derived from a grid of half-integer values. It is found that the approximate method, which avoids excessive special computation, yields inferences indistinguishable from those based on…