Result for 1EC8F448EFAD5B03A07F563199193085A8AE0194

Query result

Key Value
FileName./usr/lib64/R/library/rms/R/rms.rdx
FileSize3190
MD51713B7DE9D03AB0EF933DD6C94F53B49
SHA-11EC8F448EFAD5B03A07F563199193085A8AE0194
SHA-256BCDA264F898AF8B166CC81A533E1931BB5E8ECF3E95A37B05CEC39F0F4E65CD8
SSDEEP96:x4lDRFrJ7FzdnzB0Rz+sb2Fhw9bAL3NF0Eks4:2lRTzygst8Gs4
TLSHT172616C1F7954AF74D4206E10C3CE7C6C5C8DE5A73D43E2E83705461832D6C2C4786D45
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
MD5FCE163A75946A60B04651CC161DA4277
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
PackageReleaselp152.3.20
PackageVersion4.2_0
SHA-141432BF47B6CA61B6B82732E675F8D2A1522E688
SHA-2567392F255E6F0A112A3E34EAA3BA86ADD3E5E1B6FB55F2B521C269BB16F27E6A6