ma.test: p-value for an association score.
In matie: Measuring Association and Testing Independence Efficiently

Description Usage Arguments Details Value Author(s) References See Also Examples

This function computes the p-value for an association score using interpolation from a precomputed table (fast - only available for the bivariate case) or using a permutation test.

1	ma.test(d, maStruct, permPartition, lookup, reps)

`d`	the data set
`maStruct`	the structure returned by a call to `ma`. Must be provided. No default.
`permPartition`	a permutation partition for the data set depending on the statistical question being asked. Defaults to the partition returned by the call to `ma`.
`lookup`	logical, if TRUE then a p-value is interpolated from a table of precomputed p-values. If FALSE then a monte carlo simulation is carried out. Table lookup is only accurate for associations on bivariate data with number of samples <= 400. By default, lookup is TRUE.
`reps`	no of repeats for the monte carlo simulation. defaults to 1000.

Computes a p value for an association from the likelihood ratio statistic computed by ma. Uses interpolation by default for bivariate associations, and permutation testing for multivariate associations.

Returns a real number in the range [0,1].

Ben Murrell, Dan Murrell & Hugh Murrell.

Discovering general multidimensional associations, http://arxiv.org/abs/1303.1828

ma

    d <- shpd(n=100,m=2,Rsq=0.2)
    aScore <- ma(d)
    ma.test(d, aScore)
    # or set lookup to FALSE if you have computing time available
    # ma.test(d, aScore, lookup=FALSE, reps=10000)