prim-package: Patient Rule Induction Method (PRIM)

In prim: Patient Rule Induction Method (PRIM)

Patient Rule Induction Method (PRIM)

Description

PRIM for bump-hunting for high-dimensional regression-type data.

Details

The data are (\bold{X}_1, Y_1), \dots, (\bold{X}_n, Y_n) where \bold{X}_i is d-dimensional and Y_i is a scalar response. We wish to find the modal (and/or anti-modal) regions in the conditional expectation m(\bold{x}) = \bold{E} (Y | \bold{x}).

PRIM is a bump-hunting technique introduced by Friedman & Fisher (1999), taken from data mining. PRIM estimates are a sequence of nested hyper-rectangles (boxes).

For an overview of this package, see vignette("prim") for PRIM estimation for 2- and 5-dimensional data.

Author(s)

Tarn Duong <[e-mail]>

References

Friedman, J.H. & Fisher, N.I. (1999) Bump-hunting for high dimensional data, Statistics and Computing, 9, 123–143.

Hyndman, R.J. Computing and graphing highest density regions. American Statistician, 50, 120–126.

prim documentation built on April 3, 2025, 6:17 p.m.