Result for 4DCC1EAF5CEA8B5190AEBD5C5A71FBD48378B34E

Query result

Key Value
FileName./usr/lib64/R/library/brglm/Meta/package.rds
FileSize1122
MD50CBAEFCD8A70D4897F08D50B4976EB17
SHA-14DCC1EAF5CEA8B5190AEBD5C5A71FBD48378B34E
SHA-25636F0E3AA28A73BFD062EECE1E6EDB80E8A2834185919DA7443474CD9165A4335
SSDEEP24:Xagy8VzyopUjT+1SxYL3nCBmwfALj5NlXrs46adi3XDqeyedpt/:Xc8VUn+0xYC8aAPy466R4t/
TLSHT18F21B902967395C412E6CF727B4795BB05D2043395961E55ECB5B8877941078C26F8BC
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