Result for 02A59833F6B60087DEA0BEFF4332783AE21EA71C

Query result

Key Value
FileName./usr/lib/R/site-library/party/R/party.rdx
FileSize2800
MD538600F065DD000BFFE45C6C438DDED23
SHA-102A59833F6B60087DEA0BEFF4332783AE21EA71C
SHA-256BCD9E078959C1CF7E8231BC58B0E8DFE6D85F3D5B46737FA6C7F1FF7853E3D33
SSDEEP48:XSaJI5zfQgcTcXTJtqSGNTo8M95s0xLX5+Xl/CMLateLLeGD6lrzuomCYq:C8INeYXfqSGNTKpX2VLhLVD0rzfm3q
TLSHT185514CD7E741CD4479CF41D1991EA8485FDF1035CB2B0AE148253DB0238DAA22DB66FE
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
FileSize1128664
MD500525CADC3B7101D9BE87E521D5F658A
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-1E84855F81179ACD5222F5D897F2B73EB5ED21096
SHA-2567E78F14ABA56B5CAB5AA9A7CDBD17638DEAC06AE827635D534CEF4C3FBBEE1F5