Result for 1B110791F950561F402668AFCA70F38EEB63CF64

Query result

Key Value
FileName./usr/lib64/R/library/rms/Meta/package.rds
FileSize1292
MD588534F8FB3FA59BD57A04875D8C2F085
SHA-11B110791F950561F402668AFCA70F38EEB63CF64
SHA-2566239E56BCEF29A2DAAADD9C60C66DDA324B750F781A4C5C9146B67D35E04007C
SSDEEP24:XF14pJH6vt0+/XMOFoZ2O28rx6Vvlp/9H/r9x8u6LrLV4Tnyo/3U0DWgqAlLtYA+:XF1A6vt50rYlplH/r83Bo/kdgq8LtsS4
TLSHT19F21EA8529B58583D73DD4BA970C1809A02998579589716D51BACD1F08E72108A8E3BA
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
MD5C990591E1715898CDEE60D25D57B4D32
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
PackageReleaselp153.3.13
PackageVersion4.2_0
SHA-10469544E8FE0786B360396EA3B76391D1555A1A3
SHA-256054BFAB29950A86A3F7D0FFCB7884CCE57EDBE042757E26A4045F4BEFFD297F2