wasser.test: Statistical Test with Wasserstein Metric

In ymatts/D3M: Two Sample Test with Wasserstein Metric

Description

Statistical Test with Wasserstein Metric

Usage

wasser.test(cases, control, test.stat, paranum = 101, bsn = 5000, q = 2,
  seed = 100)

Arguments

cases	name of case group data (matrix sample * feature)
control	names of control group data (matrix sample * feature)
test.stat	test statistic
paranum	the number of quatile discretization + 1. Default is discretized by 1 %.
bsn	the number of resampling. Default is bsn = 5000.
q	power of Wasserstein metric. Default is q = 2.
seed	seed for random generator.

Value

list of p-value and test statistics.

Author(s)

Yusuke Matsui & Teppei Shimamura

References

Yusuke Matsui, Masahiro Mizuta, Satoru Miyano and Teppei Shimamura.(2015) D3M:Detection of differential distributions of methylation patterns (submitted). BIORXIV/2015/023879.

Antonio Irpino and Rossanna Verde.(2015) Basic Statistics for distributional symbolic variables: a new metric-based approach. Adv.Data.Anal.Classif(9) 143–175

Examples

nrep <- 12
cases <- Map(rbeta,rep(30,nrep),rep(1,nrep),rep(5,nrep))
cases <- do.call("rbind",cases)
control <- Map(rbeta,rep(30,nrep),rep(1,nrep),rep(5,nrep))
control <- do.call("rbind",control)
d <- wasserMetric(cases,control)
testRes <- wasser.test(cases = cases,control = control,test.stat = d)

ymatts/D3M documentation built on May 4, 2019, 5:30 p.m.