Result for 054DF6E1C26500103DF6F1ED6496EB576E9C3DD7

Query result

Key Value
FileName./usr/lib/R/site-library/Design/html/bootcov.html
FileSize20536
MD521695B8B07716710A23A02DCE6D7E0BB
SHA-1054DF6E1C26500103DF6F1ED6496EB576E9C3DD7
SHA-25631BB1069520039EE637EC81000F0D6480ED610616EE34A965DF30048B23AA5E6
SSDEEP384:4yNArxDA4AeAGtDADizr9wKVA5aDH8GxAAXhI76Wr76lB6EN69Ye:pNOD5n5D+er9wOGaTNxvhI76lB6Eoee
TLSHT1DE92C611A3C907661611C0BDE61EA8A837CFC16073E215C07E4FEB3D938646D97BB69E
hashlookup:parent-total3
hashlookup:trust65

Network graph view

Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize834506
MD533811BECABFD2D741E9B6EF65E592362
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://hesweb1.med.virginia.edu/biostat/s/Design.html
PackageMaintainerDirk Eddelbuettel <edd@debian.org>
PackageNamer-cran-design
PackageSectionmath
PackageVersion2.0.8-1
SHA-110668AA0B27555C5A0CF5D044FAB123406BE34E2
SHA-256B7A59C282FACEE52D6BD74B322A90E1D6F3E43C7C19484175E93E43874095FB4
Key Value
FileSize836968
MD5024242A947C03132AFBD892899DBAE6F
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://hesweb1.med.virginia.edu/biostat/s/Design.html
PackageMaintainerDirk Eddelbuettel <edd@debian.org>
PackageNamer-cran-design
PackageSectionmath
PackageVersion2.0.8-1
SHA-1299F0590769B9D676C14859206AD099328710F13
SHA-25602AF6E1B8D73D5272E2A1915ED502590ED22C16DC9B9915B65ABF6EE9C420903
Key Value
FileSize834628
MD5A99775E199297496250118C40AA66961
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://hesweb1.med.virginia.edu/biostat/s/Design.html
PackageMaintainerDirk Eddelbuettel <edd@debian.org>
PackageNamer-cran-design
PackageSectionmath
PackageVersion2.0.8-1
SHA-1007828E2FD536FF059CB8C40CC2EC4EF1E847A3D
SHA-25688B5B37861770BA6CEBBA7E53DC9884EDCF56546B57F92682733007351CC6C4C