Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	997478
MD5	D87296149A80780A5D398AB40F18CEFB
PackageDescription	GNU 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.
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-rms
PackageSection	gnu-r
PackageVersion	4.2-0-2
SHA-1	B347284C06654B429A378B2B930AAB89DCE65200
SHA-256	3F652243E693B8B62CCB1345F49A1EDF1DCE4AF04117A12D4B3BFBD346C887C8

Key	Value
FileSize	995458
MD5	899209E3D24C6D2F15C3184F80A2EC3A
PackageDescription	GNU 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.
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-rms
PackageSection	gnu-r
PackageVersion	4.2-0-2
SHA-1	C8B91449633905C04AD4EFBBBF41582B510AE657
SHA-256	C56091B9BA874057842C5A39FCB0FA7FEC46B7308C3FCEA642DA507204FACDFD

Key	Value
FileSize	998344
MD5	EBBDF658900B4C36FB0C4C731DF6B281
PackageDescription	GNU 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.
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-rms
PackageSection	gnu-r
PackageVersion	4.2-0-2
SHA-1	A6AD42D5FD453AC0FB6249E21976FE2227D23D62
SHA-256	C8F79950885A8DE3AAB88F619CF0502FBE86C7DEE632FC2112642756447CE63F

Key	Value
FileSize	994642
MD5	A461664C6D207D06A5734E37BCE4BED7
PackageDescription	GNU 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.
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-rms
PackageSection	gnu-r
PackageVersion	4.2-0-2
SHA-1	1699F39177BAA7746AD892E4BAEECBD3363E7553
SHA-256	41088618A9F6B27C3530D4A7ED33E2F1F85AF9AE9B07164F2DA71FE1E4B9FE87