Parents (Total: 45)

The searched file hash is included in 45 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	925044
MD5	2FD2A14565E911276355FB96B7866306
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	Ubuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.1-1-2
SHA-1	0471FE7F98FD443C148E8E4EC6BA407908732D70
SHA-256	004837D63C0C238B2F6AA50C3B20C0AD91696FCDF010C179A9688CD6A1CE29E3

Key	Value
FileSize	925098
MD5	8F9EDB554A8E6CBE831EBE4F72B07502
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	Ubuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.1-1-1
SHA-1	08025C176DFBBD0BC7BF5AECEDD183A177622CCF
SHA-256	5C808CE1E84FBED5CCFCF6B4E5AC3903791B896E3FE8B97DC9F26C49D7643D8F

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	928638
MD5	ED38282FA4F58091D018C83FF440FC52
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	Ubuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.1-2-1
SHA-1	14B96F13FA113BD53CFFB011A3E42C016557CA36
SHA-256	31FA509A831247017BC100ECC83A6E3F6072B390B694A26234074088ABACFD8E

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	924262
MD5	9E7EF90651E53D73972D876D128D6F81
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	Ubuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.1-2-1
SHA-1	2523A671E27B9BE426B3904FB01FB2D1BB077FB2
SHA-256	97014436F3D8AD971D937B5785C62A96C2AF156969F540285E9491B439AE5C93

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