hi,
-- my searches for how to perform a linear hypothesis test after a glm call turned up nothing (i can't seem to find any documentation of glm.jl other than readme.md on github) say i estimate glm(y ~ x1 + x2) is there a canned command that i can use to perform a (wald) test of f.e. H0: x1 = x2 ? more generally i am trying to figure out how to do get a standard (social science) regression going with testing, prediction, marginal effects and robust and clustered standard errors, so pointers in that direction are very welcome thanks a lot! edwin You received this message because you are subscribed to the Google Groups "julia-stats" group. To unsubscribe from this group and stop receiving emails from it, send an email to [hidden email]. For more options, visit https://groups.google.com/d/optout. |
I think your best bet would be to pycall into python statsmodels.
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On Tuesday, April 12, 2016 at 11:08:09 PM UTC+2, Ariel Katz wrote:
-- I think your best bet would be to pycall into python statsmodels. thanks, but of course not what i was hoping for my first naive go at what i had in mind, namely the following:
seems to work (sort of)
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If you need robust/clustered variance covariance matrices look at CovarianceMatrices.jl.
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On Thursday, April 14, 2016 at 10:13:09 PM UTC+2, Giuseppe Ragusa wrote:
-- If you need robust/clustered variance covariance matrices look at CovarianceMatrices.jl. thanks, indeed what i was looking for You received this message because you are subscribed to the Google Groups "julia-stats" group. To unsubscribe from this group and stop receiving emails from it, send an email to [hidden email]. For more options, visit https://groups.google.com/d/optout. |
In reply to this post by Edwin Leuven
for closure sake, the below is what i have atm
-- (it only handles single equation restrictions, but can be easily extended) i am a bit surprised that this functionality is not already available comments welcome of course, i'm new to julia
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