Result for 1A1A049DF692B0FFA32B72F946C64A01BC71E95C

Query result

Key Value
FileName./usr/lib64/R/library/brglm/Meta/package.rds
FileSize1273
MD5D41C99D0EE5B5F27344B47D734EEB77B
SHA-11A1A049DF692B0FFA32B72F946C64A01BC71E95C
SHA-2568E951A8976AB555B2D9A44D8B9BF8351770873544B1AA35B988E78A1C9B3CB20
SSDEEP24:XyeRhbKNjQlX3GUXT8sHWD5AlXAbQPWokamvnFmEb:XyeRA4nGUXZkNbaDwvF/b
TLSHT16C214A3A87F9165B0BC0A2B00AB04327EE49D01CCFA0A4F08368E401A3F87C0C7D1ABC
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
MD57389C6FD4277CCE7A66A28074DE5A001
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
PackageReleaselp152.1.4
PackageVersion0.7.2
SHA-1CC22F98B1C96CD6BB1024795C76184A812437EE8
SHA-25669049302FA2907C172D28E3B7AFB09F6C6886EBFB3EDB40834B9BB2A40F68EA0