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I 型删失下 Weibull 分布参数的估计AI 解读

The authors propose estimators for the shape and the scale parameters in the Weibull distribution under Type I censoring. They derive exact moments of the estimator for the shape parameter and establish the joint asymptotic normality of both estimators. The proposed estimators, compared with the corresponding maximum likelihood estimators, provide a simpler procedure while maintaining high asymptotic relative efficiencies for a wide range of censoring levels. Estimation of…

摘要暂缺

The modified form of the Cramér-von Mises statistic is employed for the problem of testing exponentiality with type I censored samples, in the presence of an unknown scale parameter θ. The asymptotic distribution of the Cramér-von Mises statistic is established when θ is estimated by its maximum likelihood estimator θ^⁠. Percentiles of the asymptotic distribution are obtained for various levels of censoring.

相关数据的位置参数估计量AI 解读

Asymptotic properties of an estimator of location, Jn, which is an asymptotically best linear unbiased estimator for the location parameter of the logistic distribution, are studied for dependent data. It is shown that Jn is asymptotically normally distributed for strongly-mixing dependent data. The asymptotic variance of Jn is obtained in general and computed for strictly stationary first-order Gaussian autoregressive processes. The performance of Jn for dependent data is…

寿命试验中时间截断指数分布参数的估计AI 解读

This article proves the asymptotic unbiasedness and consistency when the sample size of the maximum likelihood estimate of the mean θ of an exponential distribution in a time-truncated experiment is random. Convergence of to with μ and σ2 independent of x is established. Asymptotic normality is the same under both the conditional and the unconditional distribution, but our procedure and normalizing constants differ from those in Bartholomew (1963).