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威布尔分布参数的百分位数估计量
Large sample estimation of the location and the scale parameter of the Weibull distribution, when the shape parameter is known simultaneously, is considered. Best linear unbiased estimates based on k = 2, 4 and 6 sample quantiles are used. The optimum spacings of the sample quantiles, the coefficients to be used in computing the estimates and their variances and asymptotic efficiencies are given.
Weibull 分布参数的百分位数估计量
Large sample estimation of the location and the scale parameter of the Weibull distribution, when the shape parameter is known simultaneously, is considered. Best linear unbiased estimates based on k = 2, 4 and 6 sample quantiles are used. The optimum spacings of the sample quantiles, the coefficients to be used in computing the estimates and their variances and asymptotic efficiencies are given.
利用两个或三个次序统计量估计极值分布参数
This paper discusses the use of order statistics in ostimating the parameters of the oxtreme value distribution. The best linear unbiased estimator of the location and scale parameter is given, based on two or three order statistics, for samples up to size 20. For very large samples, the analogous estimators based on sample quantiles are obtained.
利用样本分位数估计逻辑斯蒂分布参数
Large sample estimation of the mean and the standard deviation of the logistic distribution is discussed. Best linear unbiased estimates based on k = 2(1)9 sample quantiles are used. The optimum spacings, the coefficients to be used in computing the estimates and the variances and asymptotic efficiencies of the estimates are given. A comparison is obtained between the optimum spacings and spacing the observations using the expected values of order statistics.
利用两个或三个次序统计量估计极值分布参数
This paper discusses the use of order statistics in ostimating the parameters of the oxtreme value distribution. The best linear unbiased estimator of the location and scale parameter is given, based on two or three order statistics, for samples up to size 20. For very large samples, the analogous estimators based on sample quantiles are obtained.
利用样本分位数分析超大样本极值数据
This paper deals with estimating the location and the scale parameters of the extreme value distribution when the sample size is very large, using sample quantiles. An estimator is given for the location parameter when the scale parameter is known, based on one or more (up to 15) order statistics. Also given is an estimator for the scale parameter when the location parameter is known, built on two order statistics. An iterative procedure is utilized to estimate the…