Hi R core team, I experienced the following issue with the attached data/code snippet, where the studentized residual for a single observation appears to be NaN given finite predictors/responses, which appears to be driven by the glm.influence method in the stats package. I am curious to whether this is a consequence of the specific implementation used for computing the influence, which it would appear is the driving force for the NaN influence for the point, that I was ultimately able to trace back through the lm.influence method to this specific line <https://github.com/SurajGupta/r-source/blob/a28e609e72ed7c47f6ddfbb86c85279a0750f0b7/src/library/stats/R/lm.influence.R#L67> which calls C code which calls iminfl.f <https://github.com/SurajGupta/r-source/blob/master/src/library/stats/src/lminfl.f> (I don't know fortran so I can't debug further). My understanding is that the specific issue would have to do with the leave-one-out variance estimate associated with this particular point, which it seems based on my understanding should be finite given finite predictors/responses. Let me know. Thanks!
Sincerely, -- Eric Bridgeford ericwb.me ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
