Parents (Total: 52)

The searched file hash is included in 52 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	834628
MD5	A99775E199297496250118C40AA66961
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	2.0.8-1
SHA-1	007828E2FD536FF059CB8C40CC2EC4EF1E847A3D
SHA-256	88B5B37861770BA6CEBBA7E53DC9884EDCF56546B57F92682733007351CC6C4C

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	834506
MD5	33811BECABFD2D741E9B6EF65E592362
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	2.0.8-1
SHA-1	10668AA0B27555C5A0CF5D044FAB123406BE34E2
SHA-256	B7A59C282FACEE52D6BD74B322A90E1D6F3E43C7C19484175E93E43874095FB4

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	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