MRPP-package: Multiresponse permutation procedure and its variable...

In MRPP: Multiresponse permutation procedure and its variable importance and variable selection methods.

Description

Implements multiresponse permutation procedure (MRPP), variable importance measure for MRPP, and backward variable selection procedures for the MRPP, applicable to high dimensional data.

Details

Package:	MRPP
Type:	Package
Version:	1.0-321
Date:	2013-11-17
License:	GPL version 2 or newer
LazyLoad:	yes

• mrpp.test The MRPP, a permutation test applicable to high dimensional data.

• get.dp.dw.kde Variable importance measure: approximate derivative of p-values to weights.

• get.p.dd.dw Variable importance measure: permutation p-value using the derivative of Euclidean distance with respect to weights as the distance measure.

• mrppBVS Backward variable selection for the MRPP.

• mrppBVS.test Backward variable selection nested within outer permutations.

• smrpp.test Sparse Weighted MRPP within outer permutations.

• smrpp.penWt Sparse Weights given MRPP importance measures from get.dp.dw.kde.

• permuteTrt Generate random treatment assignments.

• FR2permvec Conversions among decimal factoradic number, radix factoradic number, and permutation vector.

• HSEL.bigz Generate a random sample of size m from a large population of size n.

• bw.mse.pdf.asym Choose a bandwidth for kernel density estimation by minimizing asymptotic mean squared error of density estimate at the first data point.

Author(s)

Long Qu

Maintainer: Long Qu <[e-mail]>

References

Long Qu, Dan Nettleton, and Jack C. M. Dekkers. Relative Variable Importance and Backward Variable Selection for the Multiresponse Permutation Procedure, with Applications to High Dimensional Genomic Data. (Manuscript under review)

Examples

set.seed(2340)
x=matrix(rnorm(20*5),20)
trt=gl(2,10)
nparts( table(trt))		## 92378 partitions =  choose(20,10)/2
urand.bigz(0,seed=1032940L) # init seed
pmat=permuteTrt(trt, 5e2L)		## use 500 random permutations
mrpp.test(dist(x), trt, permutedTrt=pmat, wtmethod=0 ) ## MRPP for all variables

## Not run: 
mrppBVS(x, pmat) ## backward selection of variables
mrppBVS.test(x, pmat) ## nested permutation test with backward variable selection
smrpp.test(x, trt, permutedTrt=pmat, wtmethod=0 ) 

## End(Not run)

MRPP documentation built on May 2, 2019, 4:46 p.m.