I was wondering if someone might be able to tell me what formula R's influence.measures function uses for determining whether the hat value it computes is influential (i.e., the true/false value in the "hat" column of the returned is.inf data frame). The reason I'm asking is that its results disagree with what I've just learned in my statistics class, namely that a point should be considered influential if h_ii > 2(k+1)/n, where k+1 is the number of parameters in the model and n is the number of data points. My 2(k+1)/n value would mark at least one more point influential than influence.measures does for the data set I'm looking at.
I am using R 2.4.1 under Windows. (Upgrading is difficult due to rather severe security policies.) Thanks, --Paul ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
