Result for 5DC126014F6BB488027886BFF2E494B70D049BA7

Query result

Key Value
FileName./usr/lib/R/site-library/brglm/R/brglm.rdx
FileSize578
MD5D55649FCEA184029E38172FCE965D3D9
SHA-15DC126014F6BB488027886BFF2E494B70D049BA7
SHA-256709A5CDBB9C52A2A260C234D123BDD7066F4916308D031283B67B57D3CB84697
SSDEEP12:XUZWjL3V3UnQCbB4vugY3aW785IyebLb/K5Hb1xuuFclFuCgxGgFunq:XfL3V3UQCF4volo5Y/W1Bc3uCgxGAuq
TLSHT1EAF04132C628A910AE6CB03939C1C51566783C2B7A0AD9AA540075500BCCF922E9204F
hashlookup:parent-total3
hashlookup:trust65

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Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize123308
MD53AB2FC34ED7B59B1677CDBE260880B86
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.
PackageMaintainerDebian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageNamer-cran-brglm
PackageSectiongnu-r
PackageVersion0.7.1-1
SHA-174FF1A4B5D746F22D3C69B9D38085A001D5B86E4
SHA-25681B1AA0856B271BBE8F9EF27F31897262A125EA572F8648F08A1F5C81230A697
Key Value
FileSize123476
MD55F47FC3E8566037D705E041188BE0520
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.
PackageMaintainerDebian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageNamer-cran-brglm
PackageSectiongnu-r
PackageVersion0.7.1-1
SHA-113A6C6D50B0673D086EB140D9125C04F732FEFC7
SHA-256ED45D5BED29E958808CDC325E321A438E5A170DB297BA1253A2EEA90D2A97A55
Key Value
FileSize123400
MD59FB329F6175E0C114D9DDE970DADA699
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.
PackageMaintainerDebian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageNamer-cran-brglm
PackageSectiongnu-r
PackageVersion0.7.1-1
SHA-1B9E35C7F4036E30DF6F4B11EB03D979C635C9B6D
SHA-2561EAD7C8A4944705445E5046F1073FE2033067A191E0B10488F8193FDE273370E