R: SIGNIFICANCE TEST

sig.test {ecp} | R Documentation

## SIGNIFICANCE TEST

### Description

Performs a permutation test.

### Usage

    sig.test(D, R, changes, min.size, obs, env=emptyenv())

### Arguments

`D` | A n by n distnace matrix.
`R` | The number of permutations to use in the permutation test.
`changes` | The set of current change points.
`min.size` | Minimum number of observations between change points.
`obs` | Test statistic value for non-permuted data.
`env` | Environment with information used to reduce computational time.

### Details

Called by the e.divisive method, and should not be called by the user.

### Value

The returned value is the approximate p-value obtained by the permutation test. The permutaiton test is performed using the method outlined in Gandy (2009).

### Author(s)

Nicholas A. James

### References

Matteson D.S., James N.A. (2013). A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data.

Nicholas A. James, David S. Matteson (2014). "ecp: An R Package for Nonparametric Multiple Change Point Analysis of Multivariate Data.", "Journal of Statistical Software, 62(7), 1-25", URL "http://www.jstatsoft.org/v62/i07/"

Gandy, A. (2009) "Sequential implementation of Monte Carlo tests with uniformly bounded resampling risk." Journal of the American Statistical Association.

Rizzo M.L., Szekely G.L. (2005). Hierarchical clustering via joint between-within distances: Extending ward's minimum variance method. Journal of Classification. pp. 151 - 183.

Rizzo M.L., Szekely G.L. (2010). Disco analysis: A nonparametric extension of analysis of variance. The Annals of Applied Statistics. pp. 1034 - 1055.

### See Also

`e.divisive`

[Package ecp version 3.1.2 Index]