Result for 6699289C7D5337E2FA5A57F7AF67510135380CA1

Query result

Key Value
FileName./usr/lib64/R/library/brglm/R/brglm.rdx
FileSize565
MD58E8E4BDDEF24ED1FD35590D67F94DE0A
SHA-16699289C7D5337E2FA5A57F7AF67510135380CA1
SHA-256C92C8F507DF4F17637EA2D7EA6526BAA2E26E4239A6C86F4B48E8BC873E82D5C
SSDEEP12:XsxdR48H/pCugXbxgnYauK6NQJcoGB6HGOig5OOuMrVYGZzDUALDuiFJ:XQdDpvExgnYrKVCoGBZOisT5Yz8DuQ
TLSHT1CFF096F9750DC0E380C56C37C08762436D959AC73C130C2841B9D75FF0501421C83768
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
MD50286855345E1B2A8E09FEFF96AB19FCB
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
PackageReleaselp153.1.1
PackageVersion0.7.2
SHA-127745A2702479F4C311FA2E69524E2536D950E53
SHA-256D7F60F07C295DA20CC1A5D641CA14ACDFA8D623E998221CB22D2340921AC2C5C