Result for 5DB6DE11A0F10700ECFFDE1C0DB67C635401B532

Query result

Key Value
FileName./usr/lib64/R/library/brglm/DESCRIPTION
FileSize1319
MD537DD6F9038F7E4C6F990DEECFAC3334C
SHA-15DB6DE11A0F10700ECFFDE1C0DB67C635401B532
SHA-2566196DA1AFA06DE2D396D1A2C851DF6629D2C8E49B242C1CD5228BF4E08E4E2B9
SSDEEP24:O1CeccOA0fRrovMDhMjrmCf9cp8tJcZ2w0gxrh:OXccO5ovMDhMD+kKZiw
TLSHT1762163A67582BF7B0F0106C67B3B27E59E1D06F073F34059641C9A1C69505A712936ED
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