Result for 5F349C888F3C7E54C74ED7B3E5BDD5A5EB9C1669

Query result

Key Value
FileName./usr/lib/R/site-library/brglm/Meta/data.rds
FileSize100
MD5DA57E3463C0A8440A208D8894ED113BA
SHA-15F349C888F3C7E54C74ED7B3E5BDD5A5EB9C1669
SHA-2564E013CD30C8149C55F5B35DA86864AB4F16386D2CD8208A2AF32B3F2BB6D0632
SSDEEP3:FttVFHu9Dmyl+fz3AccUwqJIsapvl:XtVFO5mylEzQcidvl
TLSHT1D1B0120C03C06125CC010030D1D34E90536D64296055C8EB8044C21693AF49563F30FC
hashlookup:parent-total2
hashlookup:trust60

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Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize90772
MD5015DA8FA008BCA0D94173E8E00CE3C35
PackageDescriptionGNU R package for bias reduction in binomial-response GLMs Fit 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.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamer-cran-brglm
PackageSectiongnu-r
PackageVersion0.6.1-1
SHA-1846DAA5288933FF2F6E59532BBEAE13431DC3747
SHA-256096D2F0659D1F082663C33702EABD5983288BF8F1E50DC1DF69AA91A64917F08
Key Value
FileSize90944
MD5D3AA50464CEBC1542ACA0D3C5E80273C
PackageDescriptionGNU R package for bias reduction in binomial-response GLMs Fit 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.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamer-cran-brglm
PackageSectiongnu-r
PackageVersion0.6.1-1
SHA-1B9D99EB521752C8E1D3536E7877946FF9A3FF709
SHA-25609ECBBE346D9C74D05D8E67B59D35E64D7B06968736A012CCACCD17757F7FE75