Result for 7825A9024845E95B9825C83CE0434D6A32BD8277

Query result

Key Value
FileName./usr/lib64/R/library/brglm/Meta/package.rds
FileSize1122
MD59341D337D9BD834FEDBB49FAA1E41F09
SHA-17825A9024845E95B9825C83CE0434D6A32BD8277
SHA-256B248EE5ED0A3E7907E3858A36B809596FACE8FD268F6DD4A077DC99422125D4E
SSDEEP24:X7Zzf25XPvT8IzyT9CX+Jaqy/M33gnEMZmw3Swd7VeyTijcBfhd/eY:XpqXPvT8I69COoq3YEMwwxjJWY
TLSHT13321F92D6B518789A700DF135180FE174AF46E43B8E26F3A3F254B002F571AC08C7C49
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
MD505CCCA38069C76223CDC895DEFB13365
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
PackageReleaselp150.3.48
PackageVersion0.5_9
SHA-1507D00E665869828A39E7157C279194FF8FB1918
SHA-2560EE733EAF24F3DB28775BADB6FC9BA4AD4CB066AB71F0DD2BAF01389F2F4E350