Result for 078EADF4AD9281FCBE276711D9A342224D2CE7AA

Query result

Key Value
FileName./usr/lib64/R/library/brglm/DESCRIPTION
FileSize1319
MD5004F9D7825A39898D0AA24E9EECAC065
SHA-1078EADF4AD9281FCBE276711D9A342224D2CE7AA
SHA-256621A312DC71AF7C5FC0CB2CBE5C6503D54298E6E87A3EA75D39C2C1CE7B9D168
SSDEEP24:O1CeccOA0fRrovMDhMjrmCf9cp8tJcZ2w0gxr76z:OXccO5ovMDhMD+kKZin
TLSHT1EB2163A67482BF7B0F4105867B3B27E19E2D06F163E34059642C5A1C69545A312E36ED
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