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每级同时测试两个试件的小样本升降法AI 解读

A modification of the small sample up-and-down method is studied for the normal, logistic, and extreme value distributions. Two specimens are tested “in series” (i.e., simultaneously) at each stimulus level, and the decision to increase or decrease the stimulus level for the next test is made as soon as the first specimen responds. This procedure can markedly reduce the total test time in certain situations. Overall, the efficiency of the new procedure, as judged using…

极值响应分布下的小样本升降法AI 解读

Tables for computing LD50 estimates are presented for the extreme value (smallest and largest) distributions based on maximum likelihood and minimum chi-square analyses for small sample up-and-down test outcome sequences of nominal length N, 2 ≤ N ≤ 6. Overall, especially considering the small sample sizes involved, LD50 estimates based on assumed symmetrical distributions seem relatively robust to minor departures from symmetry of the actual response distribution.

小样本升降法中若干中位反应估计量的均方误差比较AI 解读

Mean square errors associated with median response estimates are compared for the normal and logistic distributions, based on both maximum likelihood and minimum chi square analyses. In broad perspective there is little difference among the mean square errors for these four estimates, regardless of sample size and stimulus level spacing. The first three of the median response estimates require an iterative numerical solution, whereas the minimum chi square analysis for the…

小样本升降法中若干中位反应估计的均方误差比较AI 解读

Mean square errors associated with median response estimates are compared for the normal and logistic distributions, based on both maximum likelihood and minimum chi square analyses. In broad perspective there is little difference among the mean square errors for these four estimates, regardless of sample size and stimulus level spacing. The first three of the median response estimates require an iterative numerical solution, whereas the minimum chi square analysis for the…