Result for 0EA5184087E8DD025B85BAE7F1193D4484529A92

Query result

Key Value
FileName./usr/lib/R/site-library/rms/Meta/package.rds
FileSize1435
MD53C0610E92EC7E852732B8ADBC313F6A7
SHA-10EA5184087E8DD025B85BAE7F1193D4484529A92
SHA-256A097E448A5B994A0544D7B37AEB81999633216FE6BDC822D4C13131C841E4491
SSDEEP24:XF3nKkXHrrYDold1HTkZL7I1LipPELAzdUP3aKM92nvFhrvoqJ9jWkdZ7Nv:XZKCHdP12oRiDzde338IF98kdZBv
TLSHT19B21C6854C649E2CC0E5B3A5301C46D7D4BE4B3722915465BA288DA23EEE161C473FAA
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize1989408
MD5E249C2B93EFF89AC47580ED0180B1D33
PackageDescriptionGNU R regression modeling strategies by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. rms is a collection of 229 functions that assist with and streamline modeling. It also contains 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. rms works with almost any regression model, but it was especially written to work with binary or ordinal logistic regression, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression. . See Frank Harrell (2001), Regression Modeling Strategies, Springer Series in Statistics, as well as http://biostat.mc.vanderbilt.edu/Rrms.
PackageMaintainerDirk Eddelbuettel <edd@debian.org>
PackageNamer-cran-rms
PackageSectiongnu-r
PackageVersion5.1-3-1
SHA-19EE530F1ACAE29022A975CAA398D12CF8038527C
SHA-25662046B0773DAF1EDCFF548C01F48731C939F8792A947953F61F49273FF7053ED