A Bayesian solution is provided to the problem of testing whether an entire finite population shows a certain characteristic, given that all the elements of a random sample are observed to have it. This is obtained as a direct application of existing theory and, it is argued, improves upon Jeffrey's solution.
This paper presents an empirical investigation of the performance of five strategies for estimating the finite population mean using parameters such as mean or variance or both of an auxiliary variable. The criteria used for the choices of these strategies are bias, efficiency and approach to normality (asymmetry).
In a previous paper, conditions have been given to compute iterated expectations of fuzzy random variables, irrespectively of the order of integration. In another previous paper, a generalized real-valued measure to quantify the absolute variation of a fuzzy random variable with respect to its expected value have been introduced and analyzed. In the present paper we combine the conditions and generalized measure above to state an extension of the basic Rao–Blackwell Theorem. An application of this...