Result for 11D90238BFC0DFBF406BC012F5570940547CFFC3

Query result

Key Value
FileName./usr/lib/R/site-library/party/R/party.rdb
FileSize401235
MD53AF89A44FFCF9A0C4091DD6B93D68787
SHA-111D90238BFC0DFBF406BC012F5570940547CFFC3
SHA-256D019046DFF31F2E6F1777A53078AF9BF116922D95A9E94BDAA2280974879CD6C
SSDEEP6144:i22RYEjpdSdxMz1UppGp9zBcgn7WbqeerUkqONfB5ajKHb7iDZxtOlMw:ixLjHSdx/UiLb1QeCYG7iDftaMw
TLSHT19884235DEF5C218EB6400C64521AD1B0641C34917944E9EE6712EA0FB6FBCA4FECC6BE
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
FileSize1121624
MD5A7E26CDE5A7C0AC5F9B89A52500ED722
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-13C8423F464F92A7F528F100312D9B888D34BEB12
SHA-2562C74C31BE18ECB0AE6830422AAD22E1DB0B9D7E25E1DEA88F829CFB1A99155FD