Result for 389A45C660F0E3255CD92917A020BAF6AC6E90D5

Query result

Key Value
FileName./usr/lib64/R/library/brglm/R/brglm.rdb
FileSize43686
MD54BC4734D4234E94B868D162C00D3BAA5
SHA-1389A45C660F0E3255CD92917A020BAF6AC6E90D5
SHA-2569A63DF95825DAA04C501D56AD670B349FE7EDC5EC934C63CF210D8D4D04CB50D
SSDEEP768:zT13XtysDCJzWHlAZcFfAPbB4tcPlnCDzIgTZon2BeOrTmsbPgOyphnf37cmZLyc:zT13XtysWJelAaFYPbB4tKpCogTa2BXW
TLSHT19F13F1BE5752984D016CF4CA45934AD1B06CADF9CBFC46287D0B437BED1E71019A7095
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
MD55973830AEB84AF8516D71EBA12EAD45B
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
PackageReleaselp152.3.12
PackageVersion0.5_9
SHA-186CB437A85653021C4DC9EABCC7ADF334FEB74A8
SHA-25624F041A5384B9CD9D2F4842E686B90E2917AF384BBD91685E737D216CC5CF119