Parents (Total: 49)

The searched file hash is included in 49 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	2104788
MD5	13AE43031465B6221CA5455844656ED9
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	6.1-1-1
SHA-1	0172754A338E12A132A0DB11A1422BE618152BD7
SHA-256	C2D6F4D8D358E4B92BB1924ACD61761EC77B08CB2B0E6E3F9DF4EFF59C0919DF

Key	Value
FileSize	1990568
MD5	3AF28D8A950C723B0EC92F92794A7431
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	5.1-3-1
SHA-1	0580025E4FFE9EC87A56241B88753553889AEED9
SHA-256	95E24A785836EC1094BE6BE9DE99136BD756ABC3E332B3AB4DAEA22E0C45BC0F

Key	Value
FileSize	1160978
MD5	8652140F25A6428143A93F9DAA64CF06
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	5.1-0-1
SHA-1	0664017BC8996E255ED1531FEF0470570F0B5605
SHA-256	138D065DE6C896178A58E7ED8E31240953AC67AF669F6502B8BCA57A2B397A78

Key	Value
FileSize	2107788
MD5	4FA25C54004278AA3505BD5E3625DEA5
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	6.2-0-1
SHA-1	076EC31D45731C6939CBF86E46E9D66ED276137F
SHA-256	55341F526DD60534D9B08E5097BF61E90A75D08164984D6BE474E848A9EEBD91

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

Key	Value
FileSize	2111092
MD5	5A0634A0DB0AFF3F20D7030EF8B3A2AB
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	6.2-0-1
SHA-1	13FF2DE29EEDAC6885E1CAFE003632A0C8940AA0
SHA-256	8EF0CAC812036226771BD7198BD1D5D85A820EA392A4844B074DC3B41EA82F0F

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

Key	Value
FileSize	2022728
MD5	3918E3C017E9E83AE1E478215E340C51
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	5.1-4-1
SHA-1	1D4C141E1F209D141F433E0B5B274426F9757102
SHA-256	CBC0C86780054AD5424C1CBC67406334A34ADE81D5B80EE4676D1464D1BDFF67

Key	Value
FileSize	2100756
MD5	9417334634D7A50D997131EBE9E401E4
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	6.1-1-1
SHA-1	1EF9ABC0D9481EC816A295F8B98682B152289D58
SHA-256	301C212714EB165954D644D446A654E96A9F18E81B57EDBE4A9F7FCC3D6398CC

Key	Value
FileSize	2106124
MD5	6FEEAE4A0A164668193AB6ED012B0C66
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	6.2-0-1
SHA-1	1F9151B69D7C334E87FE0EC291A201C5DD969F8E
SHA-256	BBEA33679FD1AE9AEEDB6E2DB3EAFB030C5F14FC6EF746EEC92EF136B9554D59