Result for 07F4E16048949D0DAE11720597AEB7274075F305

Query result

Key Value
FileName./usr/lib64/R/library/rms/help/aliases.rds
FileSize1823
MD55FBC5108F4F5808BAF3166786E5DB96B
SHA-107F4E16048949D0DAE11720597AEB7274075F305
SHA-256D9E6F5A1FAF765911EAD924BD3A350ECD8CCA242C5B9294B93D9A601991365E8
SSDEEP24:XG1dJcOvxgSPf/6mqDAbX6Q4fcG9akI15OiTER49/U01t6Jj/MZC4NlOr9WUWlWH:XijTR2uqfcsI2iTER7JTyxlOr9WUbRDj
TLSHT17231EB2D1FB49726F21A35B1814F8418CF35C4C37387DBB51C6B23590D85178155D2DB
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
MD5FCE163A75946A60B04651CC161DA4277
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
PackageReleaselp152.3.20
PackageVersion4.2_0
SHA-141432BF47B6CA61B6B82732E675F8D2A1522E688
SHA-2567392F255E6F0A112A3E34EAA3BA86ADD3E5E1B6FB55F2B521C269BB16F27E6A6