Result for 0959A946CB8B010FD671CE14BFB1F35E8685C9BC

Query result

Key Value
FileName./usr/lib/R/site-library/party/help/party.rdx
FileSize728
MD5C2FCC6EB348C1A0FFDAE43563459607E
SHA-10959A946CB8B010FD671CE14BFB1F35E8685C9BC
SHA-2568E4EA592BA2D72CA688BF5F8C369696DFAEAF6CF8B7BE864CC1D0CD380CBD118
SSDEEP12:XKceRBm9uzSDADqe28jduIlgGIz4njW0Kd5IW3xX5RaZEBULU0GY/HlKRvj+nR:X4RmuFDqe28jdDlgGK4607dZEBULoYfd
TLSHT1D901991A8F128763C083DB213613F664EB3154C023A55C5FA54E61C804C9733273D0D2
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
FileSize1158172
MD5C6EFFD0765B632463F1A929B27A2D673
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
PackageVersion1.3-5-1
SHA-15F4B65716718214E3CE338B7CED666917D967C0A
SHA-256F63C33758568DA071EA0F42F69030C5EB50A070B5D1D9A3BF1032B90C197AE4C