Result for 77D5CBCB6B7FA84D0F028AB8D0ACD60D41217972

Query result

Key Value
FileName./usr/lib64/R/library/brglm/Meta/package.rds
FileSize1124
MD5EA8B4DE542BB88786C76FEC503FCBE8D
SHA-177D5CBCB6B7FA84D0F028AB8D0ACD60D41217972
SHA-256BF3E5288D116F61B20B3DE3CEC1BDEE964B24EF6EFDC87F2C5A96C542C1962A1
SSDEEP24:XajMampWcfCSxiwCtKqmFG0RfLNJFuMXUdPhQBYn/OeekCr9axqX:XWTtcfxiHtUFRLNuMXUdZIBeRCr9yk
TLSHT1E621C602828135938C18332DD6ADD38BB41669247AAD22B127D826FD727CFA45942C2F
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