Result for 3224D8452C40AC0FFB0038E2213FDDA43A355069

Query result

Key Value
FileName./usr/lib64/R/library/brglm/help/aliases.rds
FileSize294
MD57E3C172AC3197D469D87388A5F34F6AC
SHA-13224D8452C40AC0FFB0038E2213FDDA43A355069
SHA-256EB6F52A69C4A98AF641804A2AA23FB13654BDA1997630DA199450410CC6532A9
SSDEEP6:XtAxNX7fYkOUwpWp2ut4RIxB6g7I5F93k7FZ/w03OWxQ4Eln:XkVskOEpv/xsg7I5f3k7FZI03OWxQ4M
TLSHT17DE0E73688E00074F640E56F5A27FBD86586E03983045D97B58035425B58DC7015470C
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
MD5C4C88F8E0463F6B15E01ABA7A8687134
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
PackageReleaselp152.3.19
PackageVersion0.5_9
SHA-1E51D016F37B50EE0EBDA0A6A6C40A4052ACC624F
SHA-25648896505E655F4BA96A080FCEFC4237F0C2FD74921011AEC948F45BB59206586