Result for 6F06E91C365FBA5D9F98189F63C16A1D661F2D02

Query result

Key Value
FileName./usr/lib/R/site-library/brglm/html/00Index.html
FileSize3952
MD5D869179121E5A76C720705B72178B901
SHA-16F06E91C365FBA5D9F98189F63C16A1D661F2D02
SHA-256E1484AD07AB5B3C1191D6E316F7381EBBC73A5F46A8761D2E693F74AE5D75296
SSDEEP96:1zUK4jQHYQdJQPrdi8QufkCXwxQcGQlhsUMtPQKg:LIkxU7FIhBKg
TLSHT1E481AED381C4697E424115A9A7A53DEE26E103F467465D409A7F6CFFDF026E282531C3
hashlookup:parent-total2
hashlookup:trust60

Network graph view

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
FileSize121432
MD5A51B596DEDA07266B463EF3BF1A2072E
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
PackageVersion0.6.2-1
SHA-177B34888449AD1E2479A346EBDE5200ADEB40CA0
SHA-2564471C33A34C373276DB28C0312AD85A8308A5D86763B404848FE12CEEFAE67D6
Key Value
FileSize121052
MD593268611CB2A6AA6479ABDA19A638403
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
PackageVersion0.6.2-1build1
SHA-1442A831BCCB759EF1A64DE04E7FCCCF35AF29C0C
SHA-256ED96C7ED6375CE3F03F2F22BA4F7645C84BD6707F9A6B32C68EA306187E94E02