[R] Fwd: Potential Issue with lm.influence

[Bert Gunter]

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.4567 using 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 <ericwb95 using 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.4567 using 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 <ericwb95 using 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 using r-project.org mailing list -- To UNSUBSCRIBE and more, see
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>>>> 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
>>
>

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