Result for 36512EAC50C8EAEF43683AAC5700417913136A3D

Query result

Key Value
FileName./usr/lib/R/library/brglm/Meta/nsInfo.rds
FileSize469
MD5686F8D115FD48648ABA4F9099E3486BE
SHA-136512EAC50C8EAEF43683AAC5700417913136A3D
SHA-256698B3570253E9F4952A1F9A686DD52DBED050CA5A5D7E2C7E168EAF02199CD73
SSDEEP6:XteADaN7sw3LH2JQZqAUFwzCRffDYqIL2A4580uGwRS1y1l9gb9Ul3navH6B95WS:Xk2hOLH2JQ4NsqILf458Pjl9yvU3SoT
TLSHT182F0549105A59423C7324430C32A311A730F52F11772216C41B6AE2C316856D1C40C34
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
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