Result for 453273B0C8EAFC128390EC5B59DD984CC38F2AE7

Query result

Key Value
FileName./usr/lib64/R/library/brglm/help/brglm.rdx
FileSize428
MD503DF3A198986A9CA6E2E75701E4CE55B
SHA-1453273B0C8EAFC128390EC5B59DD984CC38F2AE7
SHA-256B3B4D617388777BF71056AAF26167A5643B794C4F20F17BDC1B38D084875E7C9
SSDEEP6:XtR/WiXRLoUNcmxJE1CrqS237aTKdwHB8iTMlODLzdUXjmwekH6x7tjZc7AkyrD:XH/3BsUNcSSrWMiZ/zqKb7tjm7AkyrD
TLSHT10BE023AC3FD8520FDE401172CC51CDB61644EFD2DB10E3102584D8E70C08493C4E4028
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5C4C88F8E0463F6B15E01ABA7A8687134
PackageArchx86_64
PackageDescriptionFit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
PackageNameR-brglm
PackageReleaselp152.3.19
PackageVersion0.5_9
SHA-1E51D016F37B50EE0EBDA0A6A6C40A4052ACC624F
SHA-25648896505E655F4BA96A080FCEFC4237F0C2FD74921011AEC948F45BB59206586