Result for 54AC0B682B3A86AC118B4B1F3FE3BBA5FB314853

Query result

Key Value
FileName./usr/lib64/R/library/brglm/R/brglm.rdb
FileSize43679
MD55B159D1FD1CD68D8A40B619109AC02B3
SHA-154AC0B682B3A86AC118B4B1F3FE3BBA5FB314853
SHA-256C0A4447AD77ED86A630668097793B4A5391A687845B8289B88907F0FD36C3530
SSDEEP768:zTC3XtysDCJzWHlAZcFfAPbB4tcPlnCDzIgTZon2BeOrTmsbPgOyphnf37cmZLyc:zTC3XtysWJelAaFYPbB4tKpCogTa2BXW
TLSHT14E1301BE5B53984D016CE8CA85834AE1B058ADFD8BFC865C7D0B437BED2E7101DAB094
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
MD5D4C0DC4BA189451015B0104B2D977607
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
PackageRelease3.6
PackageVersion0.5_9
SHA-1C6F95E0AAD3BF15B5ED57CA79B53BE611EDDA51F
SHA-2560F357B9BFF78AF0759482FB6C494DB27D4570B648920042F4403F9F674377640