日期精度：到日 2 篇 · 到月 5 篇 · 到年 5 篇
系统退化及其他有限样本非参数估计问题
SUMMARY Progressive degeneration times for a system of components are estimated using discrete probability coverages. A framework is provided to unify finite sample nonparametric estimation problems.
系统退化及其他有限样本非参数估计问题
SUMMARY Progressive degeneration times for a system of components are estimated using discrete probability coverages. A framework is provided to unify finite sample nonparametric estimation problems.
对称分布的非参数估计
Substantial improvements in the accuracy of nonparametric estimates are achieved when the centre of a symmetric distribution is known. Resultant benefits for confidence bands for the distribution function are extended to confidence intervals for quantiles and also tolerance limits. When the symmetry centre is not known and must be estimated from the sample improvements in accuracy are still possible.
修订与勘误：非负随机变量均值的无分布下置信限
M. Breth, J. S. Maritz, E. J. Williams, Amendments and Corrections: On Distribution-Free Lower Confidence Limits for the Mean of a Nonnegative Random Variable, Biometrika, Vol. 66, No. 3 (Dec., 1979), p. 689
非参数贝叶斯区间估计
Bayesian confidence bands for a distribution function are converted into confidence intervals for specified population quantilea and also for the mean. Bayesian tolerance limits are similarly constructed.
关于非负随机变量均值的分布无关置信下限
M. BRETH, J. S. MARITZ, E. J. WILLIAMS; ‘On distribution-free lower confidence limits for the mean of a nonnegative random variable’, Biometrika, Volume 66
非参数贝叶斯区间估计
SUMMARY Bayesian confidence bands for a distribution function are converted into confidence intervals for specified population quantiles and also for the mean. Bayesian tolerance limits are similarly constructed.
分布函数的贝叶斯置信带
A set of recurrences is developed for computing the probability content of any prior or posterior confidence bands for a distribution function assuming the parameter of the prior Dirichlet process known. When the prior parameter is unknown and is estimated from the sample, nonparametric estimates of the probability content of the posterior bands are obtained.
非负随机变量均值的分布无关置信下限
A method for setting a distribution-free lower confidence limit for the mean of a non-negative random variable is developed, and compared with the procedure which relies on asymptotic normality of the distribution of the sample mean.
利用删失数据构造均值的非参数置信区间
Summary General Kolmogorov-type non-parametric confidence contours for an unknown continuous distribution function are converted into non-parametric confidence intervals for the mean of the distribution. It is shown how these estimation procedures may be modified to enable censored data to be handled.