Result for 0F0019AC7ABFB781FD79A437EB5AF4AE7E9ECE12

Query result

Key Value
FileName./usr/lib64/R/library/brglm/Meta/package.rds
FileSize1274
MD597641ECC2E60F27EB834C9182BE06CBB
SHA-10F0019AC7ABFB781FD79A437EB5AF4AE7E9ECE12
SHA-25602146FEF57337D47CE9DCDFD2313D265F9FB040D7AB9FFA815A18904FC40AF87
SSDEEP24:XYMeNH+7OU9ENb0VpgG2krIH864eh7Nd8n6UjrYpjMWgsmr:XYMe9UGZ0XgG2k0H864u4nxoiWWr
TLSHT19C21E7521182A5A9BBE6AD3651D10526CCB1F9C23C54233D1306AC6E589014568E81FF
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
MD5C5261CF61DC5F5DFC070A11AE84BC53E
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
PackageReleaselp154.1.1
PackageVersion0.7.2
SHA-1EE999711DC4EA8E3C24BA525E5D2F7C7C91709AE
SHA-2564A886644D8DB971EA4BD966618C998085C414B5CBE0FCFE5A460698CD1F9841D