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Eno Vangjeli 《Statistical Papers》2012,53(1):229-238
Sampling plans are a useful tool to decide whether large-size lots should be accepted or rejected. In this paper we introduce
double sampling plans by variables for a normally distributed characteristic with known standard deviation and two-sided specification
limits. These plans fulfill the classical two-points-condition on the operating characteristic (OC) and feature minimal maximal
average sample number (ASN). 相似文献
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Statistical calibration or inverse prediction involves data collected in two stages. In the first stage, several values of an endogenous variable are observed, each corresponding to a known value of an exogenous variable; in the second stage, one or more values of the endogenous variable are observed which correspond to an unknown value of the exogenous variable. When estimating the value of the latter, it has been suggested that the variability about the regression relationship should not be assumed to be equal for the two stages of data collection. In this paper, the authors present a Bayesian method of analysis based on noninformative priors that takes this heteroscedasticity into account. 相似文献
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Let X be a N(μ, σ 2) distributed characteristic with unknown σ. We present the minimax version of the two-stage t test having minimal maximal average sample size among all two-stage t tests obeying the classical two-point-condition on the operation characteristic. We give several examples. Furthermore, the minimax version of the two-stage t test is compared with the corresponding two-stage Gauß test. 相似文献
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