Parents (Total: 20)

The searched file hash is included in 20 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	911936
MD5	C79F7752EECE1E3F21A8401545B03BB8
PackageDescription	GNU R regression modeling strategies tools by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new 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. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model. . See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://hesweb1.med.virginia.edu/biostat/s/Design.html
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.0.11-1
SHA-1	0CDD8799030D46D9C398C28067859A576D438C79
SHA-256	307D42AD4F42B9FBFB9948D2BD1AAEB1D82E849105E750D737C5F4067334C676

Key	Value
FileSize	909480
MD5	F822B4A497FF97FEDBE6D3F370B08643
PackageDescription	GNU R regression modeling strategies tools by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new 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. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model. . See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://hesweb1.med.virginia.edu/biostat/s/Design.html
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.0.9-2
SHA-1	1423E59114977210AF70E876115A3A3EE1547ADB
SHA-256	6D0B466FB991FB4899C049D64E27622035F494DD103C1A792F37A2657D996589

Key	Value
FileSize	910970
MD5	885EA4452D9BB9FBCFD2793F8787C643
PackageDescription	GNU R regression modeling strategies tools by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new 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. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model. . See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://hesweb1.med.virginia.edu/biostat/s/Design.html
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.0.11-1
SHA-1	1BC315A0B24BFCEB91C261FF516D3529229E4890
SHA-256	1D3F1C0D90CB916CD3C4AD9E31995B2A8A69BDB19E928A80980744EF72EE55E7

Key	Value
FileSize	914370
MD5	FB5A40B57AEE67B46BA0FA343A8AB5CF
PackageDescription	GNU R regression modeling strategies tools by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new 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. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model. . See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://biostat.mc.vanderbilt.edu/rms and http://biostat.mc.vanderbilt.edu/s/Design.
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.0.12-1
SHA-1	2138FFC01A3E5CF46646220422DD82EAC8650D32
SHA-256	37BE65B0E0B3FDD5840829CEEDBB17B7864769DAF8D6447E820BAF9AB7197150

Key	Value
FileSize	922362
MD5	AE0126E46B9C1153AEF2A76DEAE9B697
PackageDescription	GNU R regression modeling strategies tools by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new 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. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model. . See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://biostat.mc.vanderbilt.edu/rms and http://biostat.mc.vanderbilt.edu/s/Design.
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.0.12-2
SHA-1	23061281D7A3571F2128E0D07C47E05F0695EC29
SHA-256	D502CC6CD15BF1EA31ECF6BCE7CD667EB7D058251CEA99F187EFB9AA3157AC17

Key	Value
FileSize	910836
MD5	00399CDC37A658BE765AFE19CDFAA510
PackageDescription	GNU R regression modeling strategies tools by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new 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. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model. . See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://hesweb1.med.virginia.edu/biostat/s/Design.html
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.0.11-1
SHA-1	25AD6BF400D0892AA0E2E26EFC37BB2421A282F9
SHA-256	D591C63C7B0FCCD5101066502E53753F5D3596A8941DB6936F93389FD684AD89

Key	Value
FileSize	912914
MD5	A2FB4BB54E2CE6B17CAA1E82A92C359A
PackageDescription	GNU R regression modeling strategies tools by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new 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. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model. . See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://biostat.mc.vanderbilt.edu/rms and http://biostat.mc.vanderbilt.edu/s/Design.
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.0.12-1
SHA-1	36181E6BADC656C1ABA089698C98D091AFEDEC77
SHA-256	7BDEB30AA0B48D9C19FD27490383D794BBB03434CC61D7C8B89F9D591F22A202

Key	Value
FileSize	913898
MD5	361018E941B2426740D0E70DEE1E68EA
PackageDescription	GNU R regression modeling strategies tools by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new 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. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model. . See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://biostat.mc.vanderbilt.edu/rms and http://biostat.mc.vanderbilt.edu/s/Design.
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.0.12-1
SHA-1	4DD1D496A54390A68A064148F89D5040EE4DC72F
SHA-256	E240007919C2EA36756BDE263F12C0E576B908342E6C94CA184B478AD8617336

Key	Value
FileSize	911504
MD5	6B115E7962CD630DCF0B293203BAFF1C
PackageDescription	GNU R regression modeling strategies tools by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new 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. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model. . See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://hesweb1.med.virginia.edu/biostat/s/Design.html
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.0.9-2
SHA-1	51018E951F8FFE0AD6473ADC9B263A214DFA0AA8
SHA-256	F5474356C67DCE0C5E4B7F001A713F4172B89A508324792B3D4BFE43EC536093

Key	Value
FileSize	914990
MD5	643B3B5C1B2B145DB74983574797D407
PackageDescription	GNU R regression modeling strategies tools by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new 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. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model. . See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://biostat.mc.vanderbilt.edu/rms and http://biostat.mc.vanderbilt.edu/s/Design.
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.0.12-1
SHA-1	563883B7BDF731FD9E753C6E70823B3CA3ADB600
SHA-256	8E55C73007A5F5CF2F8F5C20CAAF940F612D628E35441524C2161214F2821B89