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估计方程的偏差及其在逻辑判别错误率中的应用AI 解读

The logistic regression classification method uses parameter estimates that are the solution of an estimating equation. This article derives a convenient expression for the bias of a vector estimator defined by estimating equations. The expression and the results of O'Neill are used to derive the bias and the error or misclassification rate of logistic regression classification in two examples where the assumed model for logistic regression does not hold. Logistic regression…

估计方程的偏差及其在逻辑回归判别错误率中的应用AI 解读

The logistic regression classification method uses parameter estimates that are the solution of an estimating equation. This article derives a convenient expression for the bias of a vector estimator defined by estimating equations. The expression and the results of O'Neill are used to derive the bias and the error or misclassification rate of logistic regression classification in two examples where the assumed model for logistic regression does not hold. Logistic regression…

非贝叶斯分类规则的错误率与 Fisher 线性判别的稳健性AI 解读

We call a classification procedure non-Bayes if it does not converge to the Bayes classification procedure. An asymptotic expansion is found for the expected error rate of such a classification rule. This is used to compare the estimates of Fisher's linear discriminant rule, F, and the quadratic discriminant rule, Q, under departures from the equal variance matrices assumption. It is found that F is quite robust to departures from the equal variances assumption.

非贝叶斯分类规则的误分类率与Fisher线性判别的稳健性AI 解读

We call a classification procedure non-Bayes if it does not converge to the Bayes classification procedure. An asymptotic expansion is found for the expected error rate of such a classification rule. This is used to compare the estimates of Fisher's linear discriminant rule, F, and the quadratic discriminant rule, Q, under departures from the equal variance matrices assumption. It is found that F is quite robust to departures from the equal variances assumption.

单样本寿命表数据的拟合优度检验AI 解读

Grouped censored data are common in life testing, medical trials, and other fields. Individuals, subject to a disease, have their lifetimes recorded as belonging to a certain interval. If the individuals are censored or removed before death, then it is only known that their lifetimes were at least as great as the beginning of the interval in which the individuals were censored. A goodness-of-fit problem is to test the agreement of a hypothesized survival curve with the…

单样本寿命表数据的拟合优度检验AI 解读

Grouped censored data are common in life testing, medical trials, and other fields. Individuals, subject to a disease, have their lifetimes recorded as belonging to a certain interval. If the individuals are censored or removed before death, then it is only known that their lifetimes were at least as great as the beginning of the interval in which the individuals were censored. A goodness-of-fit problem is to test the agreement of a hypothesized survival curve with the…

分类程序错误率的一般分布及其在逻辑回归判别中的应用AI 解读

The large-sample distribution of the error rate of an arbitrary estimator of the optimal classification rule is given. The asymptotic distribution of the logistic regression estimator is found. These results are used to show that the efficiency of logistic regression classification in some nonnormal cases is low. This suggests that maximum likelihood discrimination should be used whenever possible.

消除一种致死疾病后寿命增量的无分布估计AI 解读

An individual suffers from several lethal diseases. The cure time is the additional length of life if one of the diseases is eliminated. Some distribution-free estimators of location parameters for cure time are proposed and their asymptotic properties given.

消除疾病后延寿时间的分布无关估计AI 解读

An individual suffers from several lethal diseases. The cure time is the additional length of life if one of the diseases is eliminated. Some distribution-free estimators of location parameters for cure time are proposed and their asymptotic properties given.