伪回归，可以翻翻相关论文，看别人怎么解释的

谢谢分享……

enjoy!


When analyzing data with a logistic regression, an equivalent statistic to R-squared does not exist.  The model estimates from a logistic regression are maximum likelihood estimates arrived at through an iterative process.  They are not calculated to minimize variance, so the OLS approach to goodness-of-fit does not apply.  However, to evaluate the goodness-of-fit of logistic models, several pseudo R-squareds have been developed.   These are "pseudo" R-squareds because they look like R-squared in the sense that they are on a similar scale, ranging from 0 to 1 (though some pseudo R-squareds never achieve 0 or 1) with higher values indicating better model fit, but they cannot be interpreted as one would interpret an OLS R-squared and different pseudo R-squareds can arrive at very different values.


from

http://www.ats.ucla.edu/stat/mul ... suedo_RSquareds.htm

greene的书上有讲拟R2的

似呼可以不考虑那个指标,可不对些进行解释.只有在线性回归中才需要对R2进行解释.