Result for 0AAA9AEF8DE72DBE3EA46ED888D695E3D56E5E87

Query result

Key Value
FileName./usr/lib/R/site-library/Design/html/validate.html
FileSize6614
MD507D5C32CF06099AB293EF3C040EADB88
SHA-10AAA9AEF8DE72DBE3EA46ED888D695E3D56E5E87
SHA-25618511A3A5E6D3CFE5AA94F11F1739ADB29153774502E785875B99BA0450FC6A6
SSDEEP192:3IaOiHpPV/wYxxa6Jhgc9MYrO++nPgWUhl5k5wp:3IBiHpP31wc9MuO++IWUhlq5wp
TLSHT174D1A306A2C107121C04C1FEF790AC9676DF4254FBE125C07D0EE76A968EBA4423E78F
hashlookup:parent-total5
hashlookup:trust75

Network graph view

Parents (Total: 5)

The searched file hash is included in 5 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize914372
MD530A9955A0085D477EFC1FDA8EFFFC7C4
PackageDescriptionGNU 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.
PackageMaintainerDirk Eddelbuettel <edd@debian.org>
PackageNamer-cran-design
PackageSectionmath
PackageVersion2.0.12-2
SHA-1C65B39851C6296EC44512396C63CF62091B8E036
SHA-25652802F3942917D98F5C2B17463FABF9189B00BABD6669A98BBB63E889CC011F8
Key Value
FileSize918960
MD5C5E7820B612A8136D4AE47AF03AB0500
PackageDescriptionGNU 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.
PackageMaintainerDirk Eddelbuettel <edd@debian.org>
PackageNamer-cran-design
PackageSectionmath
PackageVersion2.0.12-2
SHA-16AE24643A462E7A30580BFC618391F68EFD6A8AB
SHA-25608138438A6232078DA27A358BB32BFFD2F6DC9CB9D0C382B4F37E1EAB2E54AC2
Key Value
FileSize915454
MD589F7B20F42C0B34084BEEE969018DFC2
PackageDescriptionGNU 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.
PackageMaintainerDirk Eddelbuettel <edd@debian.org>
PackageNamer-cran-design
PackageSectionmath
PackageVersion2.0.12-2
SHA-1D1E20DFC53C592777526C3237A39DA61DEFECDA8
SHA-256FD1F87A389E1124D31DC57961211CBAF61E270F390422C3A532D0EC310542C14
Key Value
FileSize922362
MD5AE0126E46B9C1153AEF2A76DEAE9B697
PackageDescriptionGNU 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.
PackageMaintainerDirk Eddelbuettel <edd@debian.org>
PackageNamer-cran-design
PackageSectionmath
PackageVersion2.0.12-2
SHA-123061281D7A3571F2128E0D07C47E05F0695EC29
SHA-256D502CC6CD15BF1EA31ECF6BCE7CD667EB7D058251CEA99F187EFB9AA3157AC17
Key Value
FileSize916102
MD53DFD0579BD8FD31BA23C2A321B4F9E3A
PackageDescriptionGNU 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.
PackageMaintainerUbuntu MOTU Developers <ubuntu-motu@lists.ubuntu.com>
PackageNamer-cran-design
PackageSectionmath
PackageVersion2.0.12-2
SHA-1ED476196E3F269BE84D321DB8907625A42CE0F26
SHA-256452DD58BB63035A034101F94F776AB090DB3DE530E0ECA31EA72BBC867F48D8C