Result for 29F76E6995443F2CE10E9A984EA5E49634CEA9C5

Query result

Key Value
FileName./usr/lib64/R/library/mi/R/mi.rdx
FileSize3775
MD5F01C46154C267603DEFDFF9720178A94
SHA-129F76E6995443F2CE10E9A984EA5E49634CEA9C5
SHA-2561F66B794324C0B8C22FEFB247517C53B6AE7E3209BAFB4A68209325D7787535F
SSDEEP48:XXR8AS4Meeeq6r1M+C/MSIjx94yi8/3RL3aB8Iy4EQ05jE414HfTYlsRaS8luUzY:HeAAeeelJMdCx3/3sBczr1EkeRavluBN
TLSHT1B5717B15EF6180BCD27F807F70487A480E9FB166C66212F538DE9D2B797E909D20C921
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
MD580524E5A535BD8744237ADFFD3A9D508
PackageArchx86_64
PackageDescriptionThe mi package provides functions for data manipulation, imputing missing values in an approximate Bayesian framework, diagnostics of the models used to generate the imputations, confidence-building mechanisms to validate some of the assumptions of the imputation algorithm, and functions to analyze multiply imputed data sets with the appropriate degree of sampling uncertainty.
PackageNameR-mi
PackageRelease11.6
PackageVersion1.0
SHA-1F56DEB51BEB462609026C4F9DA9280319B565E54
SHA-256E4D7A4C3AB8F2BE74730C95DC82F21DFD80017D238D1A7485B15DE6A27C51BB7