Result for 219B05E7BCA04EC6885BF6F46B4602D90D258ABC

Query result

Key Value
FileName./usr/lib/R/site-library/party/DESCRIPTION
FileSize2525
MD53EAFBAFB5B631A706E93F9BB754FCF03
SHA-1219B05E7BCA04EC6885BF6F46B4602D90D258ABC
SHA-256F0F218D63B02B89B70A952FC358C58BFB0EBBCDA56B93FC046060CB43EE9EF35
SSDEEP48:I/KdNi08rwt5YvjUbp99yBpGouP9UQJr95NxT1B1Ll+XnmaPo6jmLoL:I/K7i0ywjYbYvM8P9TJrfX1Z+XmaTioL
TLSHT11451A4027C706581778BE2583666A609B3AF615C7EB9386C726C44780B3ED5C4AFB74C
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
FileSize1133224
MD53183036710F01F60E546F36855302F52
PackageDescriptionGNU R laboratory for recursive partytioning A computational toolbox for recursive partitioning. The core of the package is ctree(), an implementation of conditional inference trees which embed tree-structured regression models into a well defined theory of conditional inference procedures. This non-parametric class of regression trees is applicable to all kinds of regression problems, including nominal, ordinal, numeric, censored as well as multivariate response variables and arbitrary measurement scales of the covariates. Based on conditional inference trees, cforest() provides an implementation of Breiman's random forests. The function mob() implements an algorithm for recursive partitioning based on parametric models (e.g. linear models, GLMs or survival regression) employing parameter instability tests for split selection. Extensible functionality for visualizing tree-structured regression models is available. The methods are described in Hothorn et al. (2006) <doi:10.1198/106186006X133933>, Zeileis et al. (2008) <doi:10.1198/106186008X319331> and Strobl et al. (2007) <doi:10.1186/1471-2105-8-25>.
PackageMaintainerDebian R Packages Maintainers <r-pkg-team@alioth-lists.debian.net>
PackageNamer-cran-party
PackageSectiongnu-r
PackageVersion1.3-9-1
SHA-15B65F7212B83829E135737D5582AB1E3295E3D76
SHA-256DCCF2CA6F71C546A95694CD2E6B056A7ED0B47D2F13BDBD9F31DE5DFEF8CEC6D