Result for 6884FB0F35D6CC908E5CD89F9877EA5FB03D1E5F

Query result

Key Value
FileName./usr/lib/R/library/brglm/R/brglm.rdb
FileSize43677
MD5AA89376DBD5027BA26352E043D918F6C
SHA-16884FB0F35D6CC908E5CD89F9877EA5FB03D1E5F
SHA-256A6BF00A04E59FD5B42D0949AAC1693501957B40C8C9C501610541374AAB4DA06
SSDEEP768:zTt3XtysDCJzWHlAZcFfAPbB4tcPlnCDzIgTZon2BeOrTmsbPgOyphnf37cmZLyc:zTt3XtysWJelAaFYPbB4tKpCogTa2BXW
TLSHT1D91301BE5752984D016CE4CA95834AD2B06CADF9DBFC861C7D0B433BED1E710199B095
hashlookup:parent-total1
hashlookup:trust55

Network graph view

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
MD5DADAB67A63468319DE624AC1F9E9270C
PackageArcharmv7hl
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
PackageRelease3.181
PackageVersion0.5_9
SHA-1E1418144096C01506951904A8E9D9C6C63F16D05
SHA-256093D7FC9E2E0E8C3849BB70087382299EDCCC03D91CE43789CEE8A458080E895