Result for 11330AE1D35BCCA563331B1A13195FA2538F524B

Query result

Key Value
FileName./usr/lib64/R/library/mi/Meta/hsearch.rds
FileSize3053
MD594C73E4056BD406AD7179FC0F2ED3C31
SHA-111330AE1D35BCCA563331B1A13195FA2538F524B
SHA-25646C27C968977C151FED2EC6FCA58E94A1808DBA54858A0A5A1D08A5FE455CEFB
SSDEEP48:XdxbQ0seOo2cQ9IgZJjguax9YSA796P7T0PNHuyjQxk/9pWMqDfsOmTdoq+dLGEl:NxU0sRLNJ0HgAcPgy0U9vHhoq+F
TLSHT1D4518DDC2F69127496D8EDD5D0640E10B6510188881E83EB878B72872DAA39C6DC8F8A
hashlookup:parent-total4
hashlookup:trust70

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Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD58FBF2E7AB9BD82C4A2D722A523223485
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
PackageReleaselp152.11.2
PackageVersion1.0
SHA-14656E22A9E84310520B5272E22B72D8C6AB0B7F5
SHA-256ED9B82949174978FDC9E596CBB801B98D2544C1B054E1EC252F0B3886CC62EA2
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
Key Value
MD5BCE3FE98ECFF80D24F40E4723E0CE3FA
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
PackageReleaselp154.11.1
PackageVersion1.0
SHA-1B9E67BA26F071D4D1E61CD4DCA16AEC99C46C270
SHA-2566670FA2A6A16A5432C37AE3F21CED17284EFDFB35A53797C010588677EC05A6F
Key Value
MD539A6493DBDBCEF30122A8B5E56097011
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
PackageReleaselp153.11.2
PackageVersion1.0
SHA-1D186B7A4DA5FDE3B0A0C27BCAE8C993B4473143F
SHA-25632D9033F6992ED2A683BB956D8E4CEDA993E4F0BE51A5A53701FBE60BA1ACAF8