Result for 13B5C5C686753DD7D500147FE4754BDCD3EF2201

Query result

Key Value
FileName./usr/lib/R/site-library/party/R/party.rdb
FileSize399671
MD5FDB1FA5C7C158BF98FBA9DA2F4A8F663
SHA-113B5C5C686753DD7D500147FE4754BDCD3EF2201
SHA-256C5F017A9C1A4D94BF6E69E13CC2AC1CBF6DF22E754E74F9902AB99DA6B3205B9
SSDEEP12288:umAB++l+kzmbBTE/UiqvcP9RKx+4g7EA2ZISWZ:umAR0k+5hvcP9dxQIBZ
TLSHT1A884239BC7F2524805C92FA9E5048CDE5CA77422E94C7E614141F6AE1CECA8D7386BFC
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
FileSize1164388
MD5310E3A70002AA3EB3566670F770A22EA
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
PackageVersion1.3-5-1
SHA-167B67433AE3D36BFB873B3BD119298B0945C026A
SHA-256BF55ADFE45E22B33C69BD6BDA043CA654DEDDDE852CF848E6882ABDFCC2E8182