Result for 0BDF239D55D3E874AB1B93D85DFBEA7D0CBD981F

Query result

Key Value
FileName./usr/lib/R/site-library/party/help/aliases.rds
FileSize920
MD51E61B89499EFA0DCCB0766187D25291A
SHA-10BDF239D55D3E874AB1B93D85DFBEA7D0CBD981F
SHA-256D2FE3D033F32ADA25D1AE543575126DA1031B6002B8D53084FDE041672EA9A16
SSDEEP24:Xn8YVyqC+C+0dV+x2krNcQnBYAjQbuvlOCf6epg6Vk1dHrF/t:Xn8Eo+/0du2kBcUPjjOC/S6Vk7pt
TLSHT16511C4D589E78CE2EBBCD183EE648CA480007346CCAA8055B84B19283E218A37CDC032
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
FileSize1091220
MD58210A3616740D6BFB29283C4D054FC82
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>.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamer-cran-party
PackageSectiongnu-r
PackageVersion1.3-3-1
SHA-1A23D4D5077825E0F3DB6D4B3A147B0E891A353B3
SHA-256389AB085C89FE5C560F22AD822A19F69201DD2F4ADEAEA874960A714FD9B19A9