Result for 686B473A23030392D5A906714A5A4100F7CE19E7

Query result

Key Value
FileName./usr/lib/R/library/brglm/Meta/package.rds
FileSize1104
MD531D98B7A1D9BDBD3C946565F30BD8330
SHA-1686B473A23030392D5A906714A5A4100F7CE19E7
SHA-2566FCBA617953DAC9B4C231D92E64630315664D092F97F0A8534E4502B19F1D30A
SSDEEP24:XVScqFbYa2LWRnIj3l8dT3ya0ljSySOTLFHzEUVscEi6:XiFkLGnIjV8QXyOTBHZHEi6
TLSHT10C11F9CCB4834897C601E77011059F1F3CF8680A00E97A56987B8592836DB26968CC2B
hashlookup:parent-total1
hashlookup:trust55

Network graph view

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
MD51844F770F3A391FEE4FFF98594E3E7E0
PackageArchi586
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
PackageReleaselp150.3.5
PackageVersion0.5_9
SHA-1054928618816F0338B95569E9A4ED25664599750
SHA-256F02413D347C51B95A250E1891811782A9FCF93D50541B34F58F0A09E058C6BAC