日期精度：到日 4 篇 · 到月 0 篇 · 到年 0 篇
逻辑回归检验的局部渐近最优设计
Design measures maximizing local power of asymptotically uniformly most powerful (AUMP) tests about the value of logitP outside the observation space are characterized.
基于近似 Bahadur 斜率的卡方拟合优度检验比较
The Pearson-Fisher $\chi^2$ statistic is asymptotically chi-square under the null hypothesis with $M - m - 1$ degrees of freedom where $M =$ number of cells and $m =$ dimension of parameter. The Chernoff-Lehmann statistic is a weighted sum of chi-squares and the Kambhampati statistic is $\chi^2$ with $M - 1$ degrees of freedom. The approximate Bahadur slopes of the tests based on these statistics are computed. It is shown that the Kambhampati test always dominates the…
Chernoff–Lehmann 卡方统计量中的分组单元选择
The approximate Bahadur slope of the Chernoff-Lehmann $\chi^2$-test-of-fit to a scale-location family on $R^k$ is computed. The goal is to select cells (whose number is independent of sample size) to maximize this slope. The supremum is found and is shown to be a maximum only in trivial cases. If the $\sup$ is finite there is always a best selection for a fixed number of cells. Equally likely cells are shown to be admissible when the alternative is large.
一般卡方拟合检验的统一大样本理论
We present a unified large-sample theory of general chi-squared tests of fit under composite null hypotheses and Pitman alternatives. The statistics are quadratic forms in the standardized cell frequencies, and we allow random cells, $k$-variate observations from not necessarily continuous distributions, and quite general estimates of unknown parameters. Generalizations of published results on a number of specific chi-squared tests follow.