Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	1163844
MD5	8D6D2CA3AEF3869FC34BE4A04D7564B0
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	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	r-cran-rms
PackageSection	gnu-r
PackageVersion	5.1-2-1
SHA-1	A8FD8BD736EFCDB96EBFECA449D256C12AAB52FE
SHA-256	A91BE3D24ABA16ECA3CB7C28E1B4A493511EE8FEF8C5E11F5A7E54B915ACD6E5

Key	Value
FileSize	1163808
MD5	07D30A059ED0245E3A0354E9BF90A1DF
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	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	r-cran-rms
PackageSection	gnu-r
PackageVersion	5.1-2-1
SHA-1	0F5F276DA0603808D60463CE1D9797C72B6DC9DD
SHA-256	19B84A2F710EAA97D254D6404BF007F7664D90A2CF339C9C2BBD3D0390C74B84