Result for 124257491FA8FA1AC500BC8C5C3908E7E115CB85

Query result

Key Value
FileName./usr/lib64/R/library/rms/DESCRIPTION
FileSize1531
MD5595B6A870C64C431F8AFF02A118D3C63
SHA-1124257491FA8FA1AC500BC8C5C3908E7E115CB85
SHA-256D8EDB0B067E84BB383A5348746DDD2CF3C5C32E8F4D6BA54F4446560EAC7FE22
SSDEEP24:iKd2iRgEuu9H5VbYtqg4ZTFTO0qOV+2TcwxaWnLh8FXESSgZkqvrkxr7:FZbYFcDqOE2AxyLh9cHvm
TLSHT1F6316501B6202B30EF4F4097BFB637934725418B7B668DB66DD6F00D2B4221D17666ED
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
MD5660A40A12C958E4DBA3D24B33BB3FF3F
PackageArchx86_64
PackageDescriptionRegression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. rms is a collection of functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models, ordinal models for continuous Y with a variety of distribution families, and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. rms works with almost any regression model, but it was especially written to work with binary or ordinal regression models, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression.
PackageNameR-rms
PackageReleaselp151.3.62
PackageVersion4.2_0
SHA-1B1A4CA855016D7752C55CEDA803230F04F0B29FB
SHA-256F442F63A48ADFB22F54D4EC7D95917DB480668097666625CD8F5EB74FC856C5F