Result for 2A253CF5AA2B8BD7FD02A052E93BFF691B1919EA

Query result

Key Value
FileName./usr/lib64/R/library/brglm/DESCRIPTION
FileSize1319
MD57E252D5AD94762B651D8F4AEE810127A
SHA-12A253CF5AA2B8BD7FD02A052E93BFF691B1919EA
SHA-256F38953B482EEE8BDFB5D78DF1D092E9CEB1C92B9CA65BCD08688F5F93D7599CE
SSDEEP24:O1CeccOA0fRrovMDhMjrmCf9cp8tJcZ2w0gxr0J:OXccO5ovMDhMD+kKZi1
TLSHT1F52163A67582BF7B0F0106C6BB3B27E59E1D0AF073F34059641C9A1C69505A712A36ED
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
MD556AADE7A867F871B437C0FA66E4EA5CB
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
PackageRelease3.26
PackageVersion0.5_9
SHA-1B1D6D8B82AB45FB309F967FC9FB80DE82CE23447
SHA-2565C80E2EBB1E917A441B857D1156C799E9953EB1AF326A8E0A20BFF0D08437C3E