Result for 62F4723FDA964E606393E88EE5FB3FD60F00BE89

Query result

Key Value
FileName./usr/lib/R/library/brglm/DESCRIPTION
FileSize1317
MD5F4EF907AF563046D08927876B3BAF320
SHA-162F4723FDA964E606393E88EE5FB3FD60F00BE89
SHA-256BF8D4E25D6664C2B59CABC5E1EAB03D6BF09632FCB03B022434E8B078E4A1896
SSDEEP24:O1CeccOA0fRrovMDhMjrmCf9cp8tJcZ2w0gxrb:OXccO5ovMDhMD+kKZiu
TLSHT1A321B6A774817F7B0F410586BB3B27E18E2D06F173F38049602C4A1C695049302E36ED
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
MD5EE4F685A8202ECB56C55196782CC5AC5
PackageArchi586
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
PackageRelease3.229
PackageVersion0.5_9
SHA-189B5D80B93BEFD77A7F87E099B90450B70D49602
SHA-256E9FBDA0A20252EB609133C6F3F07F649D6EE59561106443767E2E151E2ED0BF8