Result for 9AFD6FE3300C0F0E763C3F3D776A3601238B1D14

Query result

Key Value
FileName./usr/lib64/R/library/brglm/R/brglm.rdx
FileSize587
MD58372CCCC4995E5DFAF45E6DBBEB0B51C
SHA-19AFD6FE3300C0F0E763C3F3D776A3601238B1D14
SHA-25656792BBE64123521349F5DE8878A2CBD25A10720A236816E0101CF9C532AB392
SSDEEP12:Xs5XOFMdf6HUDM7L2by63cFuIG1oy0k2Bj9E5uTiMWdRLCPh0kF4kXqg:X8e2R+dyX6G1oyz2F9fTiM2CZlFNag
TLSHT10BF0479DDD94B933E46625E59064B258044B4C82136A448197B10D752CCE1C5090166D
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
MD56CBEE56EED656AAE8AFE7C01F82ED182
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
PackageRelease1.20
PackageVersion0.7.2
SHA-187507AB50873EB366A36D93741D108CAA18B3B0B
SHA-2564D7E0A86977773F572160D66A06A72C6FE924D91CA3FB66C88D2CEBA12584AA5