Also, I suggest you read ?influence which may explain the source of your NaN's .
Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, Apr 2, 2019 at 1:29 PM Bert Gunter <bgunter.4...@gmail.com> wrote: > I told you already: **Include code inline ** > > See ?dput for how to include a text version of objects, such as data > frames, inline. > > Otherwise, I believe .txt text files are not stripped if you insist on > *attaching* data or code. Others may have better advice. > > > Bert Gunter > > "The trouble with having an open mind is that people keep coming along and > sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > > On Tue, Apr 2, 2019 at 1:21 PM Eric Bridgeford <ericw...@gmail.com> wrote: > >> How can I add attachments? The following two files were attached in the >> initial message >> >> On Tue, Apr 2, 2019 at 3:34 PM Bert Gunter <bgunter.4...@gmail.com> >> wrote: >> >>> Nothing was attached. The r-help server strips most attachments. Include >>> your code inline. >>> >>> Also note that >>> >>> > 0/0 >>> [1] NaN >>> >>> so maybe something like that occurs in the course of your calculations. >>> But that's just a guess, so feel free to disregard. >>> >>> >>> Bert Gunter >>> >>> "The trouble with having an open mind is that people keep coming along >>> and sticking things into it." >>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) >>> >>> >>> On Tue, Apr 2, 2019 at 11:32 AM Eric Bridgeford <ericw...@gmail.com> >>> wrote: >>> >>>> 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. >>>> >>> >> >> -- >> Eric Bridgeford >> ericwb.me >> > [[alternative HTML version deleted]] ______________________________________________ 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.
