Result for 022F5ED1D1C85BFE16BF71034E6CDAC3F0E17235

Query result

Key Value
FileName./usr/lib/R/site-library/party/R/party.rdx
FileSize2796
MD5F0F1785F28B2655410434FC620555B38
SHA-1022F5ED1D1C85BFE16BF71034E6CDAC3F0E17235
SHA-2568EDC37126CDF1AAEFF7387D0C777FD8CD947886AA2FBD21FF021FBBF26227DBC
SSDEEP48:XJxMdZDQ6R7H/6glrGzzN1EkB7nSVFcMV75aWS58FJWzg/RFIT9QxpFwtA/:ZSdZ5lrEEk1nSV7V75aWwaWzgc9QxvwG
TLSHT1EF515CA7409344782BBD9EFD51D76D9067E185880541E5B04B7842311DEE3A16D490C7
hashlookup:parent-total1
hashlookup:trust55

Network graph view

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
FileSize1125056
MD5F5EF1E391DE443A3CAD4D5FABC05C80F
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-13BC563215E582514241FB890BFC487C4577494B0
SHA-256129054A8E5F81BAEB4D75F69D22598CA802BB1DD63974CB948E844FC53E38419