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二元反应生物测定的稳健估计量AI 解读

Extensions of robust estimators for the location of a symmetric distribution are given for the quantal bioassay problem. Asymptotic properties of the estimators are derived. A comparison in terms of asymptotic efficiencies under different tolerance distributions is made between the Spearman-Karber estimator and the trimmed mean and Tukey biweight estimators.

定性反应生物测定的稳健估计量AI 解读

Extensions of robust estimators for the location of a symmetric distribution are given for the quantal bioassay problem. Asymptotic properties of the estimators are derived. A comparison in terms of asymptotic efficiencies under different tolerance distributions is made between the Spearman-Karber estimator and the trimmed mean and Tukey biweight estimators.

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删失数据的最小二乘回归AI 解读

The analysis for a standard linear regression model is extended to the case of data randomly censored on the right. The slope and intercept estimators are weighted linear combinations of the uncensored observations where the weights are derived from the Kaplan-Meier product-limit estimator of a distribution function. Some distribution theory for the slope estimator is given. For illustration the estimators are applied to the Stanford heart transplant data.

一种非平衡刀切法AI 解读

It is proved that the jackknife estimate $\tilde{\theta} = n\hat{\theta} - (n - 1)(\sum \hat{\theta}_{-i}/n)$ of a function $\theta = f(\beta)$ of the regression parameters in a general linear model $\mathbf{Y} = \mathbf{X\beta} + \mathbf{e}$ is asymptotically normally distributed under conditions that do not require $\mathbf{e}$ to be normally distributed. The jackknife is applied by deleting in succession each row of the $\mathbf{X}$ matrix and $\mathbf{Y}$ vector in order…

刀切法综述AI 解读

Research on the jackknife technique since its introduction by Quenouille and Tukey is reviewed. Both its role in bias reduction and in robust interval estimation are treated. Some speculations and suggestions about future research are made. The bibliography attempts to include all published work on jackknife methodology.

生物测定中平均耐受量的非参数估计AI 解读

Theoretical properties of the Spearman-Kärber estimator of the mean tolerance in a quantal response bioassay are discussed, and its limiting distribution is studied under three different limiting processes. The Reed-Muench and Dragstedt-Behrens estimators are shown to be estimators of the mean, not the median, tolerance and to be nearly equivalent to the Spearman-Kärber estimator. The limiting distributions of the Reed-Muench estimator are considered in detail.

生物测定中平均耐受水平的非参数估计AI 解读

Theoretical properties of the Spearman-Kärber estimator of the mean tolerance in a quantal response bioassay are discussed, and its limiting distribution is studied under three different limiting processes. The Reed-Muench and Dragstedt-Behrens estimators are shown to be estimators of the mean, not the median, tolerance and to be nearly equivalent to the Spearman-Kärber estimator. The limiting distributions of the Reed-Muench estimator are considered in detail.

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回归中的同时容忍区间AI 解读

Joint prediction intervals (based upon the original fitted model) for K future responses at each of K separate settings of the independent variable have been treated by Lieberman (1961). When K is unknown and possibly arbitrarily large, these results do not apply. A solution to the problem of arbitrary K is given in terms of tolerance intervals on the distributions of future observations, the intervals being (probabilistically) simultaneous in each possible value of the…