Result for 16674FED78C945C65437069DB51AF3984727099F

Query result

Key Value
FileName./usr/lib64/R/library/brglm/R/brglm.rdb
FileSize43686
MD529BEA85FA874C807DEB949226CE6B4FB
SHA-116674FED78C945C65437069DB51AF3984727099F
SHA-2565DB134D85BE67C198478E2DF99A77B85D97708993BF8A5D506DA297D51BEC6FF
SSDEEP768:zTF3XtysDCJzWHlAZcFfAPbB4tcPlnCDzIgTZon2BeOrTmsbPgOyphnf37cmZLyc:zTF3XtysWJelAaFYPbB4tKpCogTa2BXW
TLSHT1D31301BE5752984D027CF8CA85930AD1B0686DF9CBFC8628390B437BED1E7001DEB095
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
MD5B9E647E17D49571CB4D7C063518FD7A1
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
PackageReleaselp153.3.12
PackageVersion0.5_9
SHA-115E34DD893E734654A49196439D74F8E852E75EF
SHA-256DA005EB073906E220BA813B5567FD426DC2B128FAFDBDB62E999559C0C32849D