Result for 0B765A50A2A12BCE4EFD6871D90CF36A48B5CF1F

Query result

Key Value
FileName./usr/lib64/R/library/rms/DESCRIPTION
FileSize1736
MD5C788B8E36E395067A3AF95B27D55048D
SHA-10B765A50A2A12BCE4EFD6871D90CF36A48B5CF1F
SHA-2560BD5D8360CE96A6E6197AF622734530520A2EA56C930EDF41AF16739453AAD37
SSDEEP24:iK+2qhvhEl32UHk5GLVbYtqgcZTFTO0qOV+2TcwxuWnLh8FXESSoYGxnnvRl6VXv:FChvhxg5bYFgDqOE2A1yLh9oYAnTs/
TLSHT17C317441A62026719FCB40E77FFA33964BA4818B3B569D98B89AB00C1F8271C47725DC
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
MD57EF8E71C2FE0C433E8B454FDB63954EE
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
PackageReleaselp153.5.2
PackageVersion6.2.0
SHA-16DA268D682309499F3798F0AD7BA03F30D3C6F9B
SHA-256CC64B84165727CF85A4AE1BED162D72D2A77A8F323EB2A2337F8B2BD7CEB7838