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Github user asfgit closed the pull request at:
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Github user jkbradley commented on a diff in the pull request:
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Github user jkbradley commented on the pull request:
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@tgaloppo Now that my confusion is over...LGTM Thanks very much!
CC: @mengxr
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Merged into master. Thanks!
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@mengxr Changes made.
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Github user jkbradley commented on the pull request:
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@tgaloppo 2 more small comments, but after those, I believe this will be
ready. Thanks!
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@jkbradley Good call on the test suite; I have added some non-center points
to the tests. I also added the brackets to the in-comment link.
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@tgaloppo Thanks for the updates! LGTM after tests pass
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@tgaloppo thanks for verifying about the test pdf values
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@tgaloppo Thanks for the updates. Sure, the log-space computation could be
in another PR.
Just to make sure: Did you compute the PDF values in the tests using
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@tgaloppo Could you please add a description? It can be based off of the
JIRA, just enough to cover the main points of the PR. Thanks!
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Github user jkbradley commented on the pull request:
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@tgaloppo @mengxr What are your thoughts about doing the computation in
log space as much as possible, and then exponentiating at the end? I'm mainly
thinking about
Github user tgaloppo commented on the pull request:
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@jkbradley I used Octave's mvnpdf from the statistics package for the
non-singular cases; it can not handle singular covariance matrices, so I was
only able to recreate
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@tgaloppo The logic looks good; my comments are basically about clarity
(except for the log space question). Thanks for the PR!
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One more request: Could you please add a unit test with a singular matrix?
Thank you! Perhaps in a new suite for MultivariateGaussian
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@jkbradley I think performing the pdf calculation in log-space (and
providing a logpdf() method) is a good idea. Perhaps we can make this part of
transitioning
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