Parents (Total: 10)

The searched file hash is included in 10 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	2106248
MD5	EB74C1DBC0952D7809067EAEBB8ED8B8
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	F8A4F096E9258BEC7DE21BFEB0867D41D36DBBE9
SHA-256	C63116F18F0268F80469C9413495EB62F69593C62416F2B6506AB95D5D4493CB

Key	Value
FileSize	2107952
MD5	CFA85711C54250DA0217B53D744347A7
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	5AB2F8C6307C95D3BEFA657AD5AA37F76941BF58
SHA-256	A6CD545A82C8EC69E67223FBE30C95EB8EA901CC14F93C59614834A70CF08B72

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	2107560
MD5	BE90EEE6C346C65F2B6916F17AD457A2
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	C3EB01B0160C99180C788299F45C2E39BBCF23F8
SHA-256	8D2F222BFC768C9C241347D887DCB90CE80164F8BD3EF00F9ADD7E4D9BE5702C

Key	Value
FileSize	2108152
MD5	CFFE52CE3044B7909BFF94E7AC45A2EF
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	3F574E2C3FF07EC61E5260D112599B90F978E51E
SHA-256	7B86073FD2AEC6620F32E340E6F3C0A445FFD4891B5E5A09863EA2395286A539

Key	Value
FileSize	2108124
MD5	D205C7863531D3345CE4556A0ADD2530
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	D53530C99D46B7B90B3C6A3D0F82FD7A8A47B736
SHA-256	B441B7F5C5FED53312A136CF75EB337DB7A455A2BE0BA54D1062C8E53FE36C35

Key	Value
FileSize	2107864
MD5	0FFE21DC87D25C56A84BC9C5AC220B14
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	538D9F26646180A525BD52377A909032C299483F
SHA-256	F6F65D7CD57DBA441E58D4C304955BA026EBE19990ED5A5F19B195DBDF1F297E

Key	Value
FileSize	2108016
MD5	214E43E40F0BA2DF36484649037C0D10
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	8CC3FD6A8351E2F94EA5E053C1C838A354FB0769
SHA-256	CEDFED7F578532C5FA9DF1614D45CCAC8575342EA0098347CD158F0E287C0EDD

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	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