A while back I asked about getting a list of points that R considers influential after fitting a linear model, and very quickly got a helpful pointer to influence.measures(). But "it has happened again." The trouble I am having is that points marked on plots are not flagged in the output from influence.measures(), and I can't read them on the plots. I tried some successive deletion, but then other points (naturally) start to look troublesome).
Is there a good way to get a list of suspicious entries at the beginning? In this case, I am trying to help identify possible data entry errors, and I am interested in knowing what R bothered to mark up front. Perhaps the defaults should be telling me that what I want to do is silly, but it sure _seems_ like it would be helpful. Is there a way to control the threshold used by influence.measures() to get it to flag more items at one time? I am learning the hard way, so feel free to tell me that I should be trying to do this some other way. Bill ______________________________________________ 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.
