Result for 3414548915431F948E3FA3D8C25EE89A386BBD31

Query result

Key Value
FileName./usr/lib64/R/library/brglm/R/brglm.rdb
FileSize44717
MD53E77495C1E0AF88A4A22AC649A14775E
SHA-13414548915431F948E3FA3D8C25EE89A386BBD31
SHA-256B6D648F4ACB12C558259345B78D93EEEF92CDBFBF238A39A4738DDC29C079178
SSDEEP768:zTQ53XtKnoFbhr5tldLYTG4xQUaqVXDpXtE+lfrZDmoppsBurisYQrGuc0Tm+2Rq:zTU3XtKno7r5tjL0G4xQUFBD5t1tZrpP
TLSHT17513F1E9CD1558B4B0C56122C3FD1139A53E06F2F69C9C88A564AFFAE4F8B230E5612D
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
MD57389C6FD4277CCE7A66A28074DE5A001
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
PackageReleaselp152.1.4
PackageVersion0.7.2
SHA-1CC22F98B1C96CD6BB1024795C76184A812437EE8
SHA-25669049302FA2907C172D28E3B7AFB09F6C6886EBFB3EDB40834B9BB2A40F68EA0