hier.part: Hierarchical Partitioning

Partitioning of the independent and joint contributions of each variable in a multivariate data set, to a linear regression by hierarchical decomposition of goodness-of-fit measures of regressions using all subsets of predictors in the data set. (i.e., model (1), (2), ..., (N), (1,2), ..., (1,N), ..., (1,2,3,...,N)). A Z-score based estimate of the 'importance' of each predictor is provided by using a randomisation test.

Getting started

Package details

AuthorChris Walsh [aut, cre], Ralph Mac Nally [aut]
MaintainerChris Walsh <cwalsh@unimelb.edu.au>
Package repositoryView on CRAN
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hier.part documentation built on March 3, 2020, 9:07 a.m.