Result for 6A509807679A308BD07B2E2A47D46A9328D9F7FB

Query result

Key Value
FileName./usr/lib/R/library/brglm/Meta/links.rds
FileSize345
MD5828B5168E6A895675E3FEC1137DD74BC
SHA-16A509807679A308BD07B2E2A47D46A9328D9F7FB
SHA-256261BAA59479AEA153202B27D0C3496500D6FCE1D842363314BBE2D4236C573CB
SSDEEP6:XtiJDHM7WGj1WMiLUaJAASxkzGWGt5rAFmVv1pvuer0csC9C7ym5z7EAM4Lkgl:X4JDHvL5JA3xk6WGHJpvueAcsCqnzgAX
TLSHT1B9E028AB394C0136DD545311B701779F087B913004C5CB3005F851A12E35F0D9D737D5
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
MD51844F770F3A391FEE4FFF98594E3E7E0
PackageArchi586
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
PackageReleaselp150.3.5
PackageVersion0.5_9
SHA-1054928618816F0338B95569E9A4ED25664599750
SHA-256F02413D347C51B95A250E1891811782A9FCF93D50541B34F58F0A09E058C6BAC