Result for 082FF844C09291C017C6A0B9D414CC750AC2FD5D

Query result

Key Value
FileName./usr/lib/R/site-library/Design/R/Design.rdx
FileSize7781
MD5048B470BC7675F97B109A5319B1775EF
SHA-1082FF844C09291C017C6A0B9D414CC750AC2FD5D
SHA-25611AB23152CC0260D1472D2F0DC6CF197406CCF6367599ADC5D238FF72D0134FD
SSDEEP192:sdFPiy8qNKuf9Kr/LQPGu7QO1OduXByOZ1WVJV:gKy80M3QQOYiyOZ1Wp
TLSHT17EF1B85AD6200147FA89FFB184D987462770226D7FE3A385B59CA822109B7F95FC930F
hashlookup:parent-total2
hashlookup:trust60

Network graph view

Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize909330
MD52230E84B4CA450D666A0C55272F4E6DB
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
PackageVersion2.0.9-2
SHA-190755BF824BEFB664860F495B33F6A1E76F27CEE
SHA-256D9DD31E59E89E45ED292B8871EBE0817B2688433213A206C5A14C0C01B804387
Key Value
FileSize911504
MD56B115E7962CD630DCF0B293203BAFF1C
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
PackageVersion2.0.9-2
SHA-151018E951F8FFE0AD6473ADC9B263A214DFA0AA8
SHA-256F5474356C67DCE0C5E4B7F001A713F4172B89A508324792B3D4BFE43EC536093