Result for 022863ABC9052955B3FC8CA166EECB094DB5D0A5

Query result

Key Value
FileName./usr/lib/R/site-library/party/help/paths.rds
FileSize383
MD5A69270CF2143DFCAC9387948085CBEFE
SHA-1022863ABC9052955B3FC8CA166EECB094DB5D0A5
SHA-2565713E23A1B3984C1EA862BFD2894E815BA924162DC2C585EAF68DE3EFDE419E7
SSDEEP6:XtV9a97o16qm8CyXX0KGbJFQSfibljljw5BvlMj0UXgr2C4hQsbXL+GOcv8ABG4V:XdYoMqHCy4i0OjJXgr2ysbXL+PTRQv/
TLSHT1A3E0F879E02A629CA0CCCFF840AC6117BAAB3AC2880950A28204D1848F8809A22C6398
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
FileSize1126716
MD52EB41D1A84C9F14E0F2ED68FCDB0E257
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-14AA858BE406B3CDE36477ED47D987860E2259171
SHA-256226FAAF6F2A52DF0BF5C3938247FEBD21EA97E9BA3A843901ABA1CCB48ABF9F5