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正态性假设下虚拟变量回归的渐近方差
Asymptotic variances are derived for estimators of the dummy variate regression model described in [6]. The results are summarized by asymptotic covariance matrices for the regression coefficients, the estimated logarithms of odds given X, and the estimated probabilities given X. A two population two variable example illustrates the results.
正态假设下虚拟变量回归的渐近方差
Asymptotic variances are derived for estimators of the dummy variate regression model described in [6]. The results are summarized by asymptotic covariance matrices for the regression coefficients, the estimated logarithms of odds given X, and the estimated probabilities given X. A two population two variable example illustrates the results.
正态性假设下虚拟变量的多元回归
The most frequently used practical regression model is that in which it is supposed that the dependent variate is normal for given values of the independent variate. In this paper it is pointed out that another regression model of wide applicability may be furnished by the contrary assumption—that the independent variate is normal for given values of the dependent variate. The particular case where the dependent variate is a vector of dummy variables is explored in detail.
正态假设下虚拟变量的多元回归
The most frequently used practical regression model is that in which it is supposed that the dependent variate is normal for given values of the independent variate. In this paper it is pointed out that another regression model of wide applicability may be furnished by the contrary assumption—that the independent variate is normal for given values of the dependent variate. The particular case where the dependent variate is a vector of dummy variables is explored in detail.