Result for 5DC541138C3774FC161CA4ED9CF1169A2D00F341

Query result

Key Value
FileName./usr/lib/R/site-library/rms/R/rms.rdb
FileSize272326
MD505B9E0B0847AEE818A139A4B810E41BB
SHA-15DC541138C3774FC161CA4ED9CF1169A2D00F341
SHA-256EB28AE7CE15CC45AD11F8508A343631B5180502D95DE56E6F9452DEF11451537
SSDEEP6144:IvQCJ3Ut1rCngLReL/xlj09et4EN0tA4XMdYUrLFoLf4tb6:IvLJ3AJ1Fer09XCsc2gLFoLfB
TLSHT15144234C9EECC165075680020FAFE9A7FFF5A95032F02659C9A4DABD376DD062C89D32
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
FileSize998344
MD5EBBDF658900B4C36FB0C4C731DF6B281
PackageDescriptionGNU R regression modeling strategies by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. rms is a collection of 229 functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models 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 logistic regression, 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. . See Frank Harrell (2001), Regression Modeling Strategies, Springer Series in Statistics, as well as http://biostat.mc.vanderbilt.edu/Rrms.
PackageMaintainerDirk Eddelbuettel <edd@debian.org>
PackageNamer-cran-rms
PackageSectiongnu-r
PackageVersion4.2-0-2
SHA-1A6AD42D5FD453AC0FB6249E21976FE2227D23D62
SHA-256C8F79950885A8DE3AAB88F619CF0502FBE86C7DEE632FC2112642756447CE63F