Result for 1CF5CD0DFD56BA55A383FC555BBCFB9480C4FC1A

Query result

Key Value
FileName./usr/lib64/R/library/rms/R/rms.rdb
FileSize1013323
MD5F5C56D3A4A76211BBC52BCC909FAADA3
SHA-11CF5CD0DFD56BA55A383FC555BBCFB9480C4FC1A
SHA-2567EED7FAEEF0C75E2EA9B9FF412CBEB4070138C5435ABC95C3DD15F5040730B84
SSDEEP12288:jG09Wvs3lT00Y2yusUE0FkRqJGreTlvi/Jw04fBVnt+xM+WysEx8itl0Hozs:j3wsV9s/0FXI4QfYjiC20HJ
TLSHT16825332817422F3008D4EA285DF4BB23660E775425BC6E2E5591E13EDBCDE158F72BAC
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
MD5660A40A12C958E4DBA3D24B33BB3FF3F
PackageArchx86_64
PackageDescriptionRegression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. rms is a collection of functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models, ordinal models for continuous Y with a variety of distribution families, 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 regression models, 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.
PackageNameR-rms
PackageReleaselp151.3.62
PackageVersion4.2_0
SHA-1B1A4CA855016D7752C55CEDA803230F04F0B29FB
SHA-256F442F63A48ADFB22F54D4EC7D95917DB480668097666625CD8F5EB74FC856C5F