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关于多项式函数关系模型AI 解读

SUMMARY A method for obtaining consistent estimators of the coefficients in a polynomial functional relationship model with normal errors is proposed when the error covariance matrix is either completely known or known up to a proportionality factor. For quadratic functional relationships with possibly non-normal errors, we present a consistent estimator when the error covariance matrix is known. A large sample test of the quadratic against the linear functional relationship…

多重删失 Logistic 数据下均值渐近最优线性估计的算法AI 解读

An algorithm is considered for allocating an optimum spacing for the asymptotically best linear estimate (ABLE) of the mean μ, when the standard deviation πσ 0/√3 of the logistic distribution is known, based on k order statistics selected from a large multiply censored sample. This algorithm can be applied to problems of estimating the location parameter of the normal, Cauchy and extreme-value distribution when the scale parameter is known and estimating the scale parameter…

基于选定次序统计量的 Logistic 分布参数最优线性无偏估计AI 解读

Coefficients, variances and efficiencies are provided for the best linear unbiased estimates (BLUE's) of the mean and standard deviation of the logistic distribution, with both unknown, based on four order statistics with ranks giving the maximum joint efficiency among all BLUE's based on four order statistics. Asymptotic joint efficiencies are compared for asymptotically best linear estimates (ABLE's) based on order statistics with ranks determined by various spacings. With…

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