Result for 152947A66897AF613595774B468A1F75EE7841F0

Query result

Key Value
FileName./usr/lib/R/site-library/party/R/party.rdb
FileSize399669
MD5C229A7AAF22F522717B27219AA30665A
SHA-1152947A66897AF613595774B468A1F75EE7841F0
SHA-256FC2AF94B231FB98AF907F7E9351FC095685A8595C0C09482553F6C26A141711B
SSDEEP12288:uIAU+l+kzmbBTE/UiqvcP9RKx+4g7EA2ZISWZ:uIAp0k+5hvcP9dxQIBZ
TLSHT18F84239BCBF2524801C92EA4E5058CDE5D9BA822E95C6F214041F6BD18EC9CD7786FFC
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
FileSize1158172
MD5C6EFFD0765B632463F1A929B27A2D673
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
PackageVersion1.3-5-1
SHA-15F4B65716718214E3CE338B7CED666917D967C0A
SHA-256F63C33758568DA071EA0F42F69030C5EB50A070B5D1D9A3BF1032B90C197AE4C