d3m: Two Sample Test with Distribution-Valued Data
In ymatts/D3M: Two Sample Test with Wasserstein Metric

Description Usage Arguments Details Value Author(s) References Examples

Two Sample Test with Distribution-Valued Data

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d3m(cases, control, rm.mean = FALSE, rm.var = FALSE,
  paranum = max(ncol(cases), ncol(control)), q = 2, bsn = 5000,
  seed = 100)

`cases`	name of case group data (matrix)
`control`	names of control group data (matrix)
`rm.mean`	standarize each rows of cases and control to mean=0.
`rm.var`	standarize each rows of cases and control to var=1.
`paranum`	the number of quatile discretization + 1. Default is discretized by 1 %.
`q`	power of Wasserstein metric. Default is q = 2.
`bsn`	the number of resampling. Default is bsn = 5000.
`seed`	seed for random number generator.

this function is designed for two sample test based on Wasserstein metric. The function computes the the p-values based Wasserstein metric and resampling method. If rm.mean=F and rm.var=F, then statistical test is performed only based on more than 3rd order moments.

pval p-value.

test.stat test statistic.

cases case group data used in the statistical test.

control control group data used in the statistical test.

Yusuke Matsui & Teppei Shimamura

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

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)
d3m(cases,control,paranum = 101, q = 2, bsn = 1000,seed = 100)