wmr.boot: Boot strap p-values for wavelet modulus ratio

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

View source: R/mvcwt.R

Description

Performs a phase-randomization bootstrap estimate of the null hypothesis of independent time series

Usage

1
wmr.boot(w, smoothing = 1, reps = 1000, mr.func = "wmr")

Arguments

w

an object such as returned by mvcwt

smoothing

degree of smoothing; larger values give greater smoothing

reps

number of repetitions

mr.func

a function taking a "mvcwt" object to be applied to each trial

Details

The phases are randomized reps times for each combination of input variable and scale. This package depends heavily on the dopar function in the foreach package. If you do not have a lot of cores available to you, you may need to let this run overnight.

Value

an object of class "mvcwt" suitable for use with contour.mvcwt.

Author(s)

Timothy H. Keitt

References

Keitt, T. H. 2008. Coherent ecological dynamics induced by large-scale disturbance. Nature 454:331-4. doi:10.1038/nature06935.

See Also

mvcwt, wmr


thk686/mvcwt documentation built on May 27, 2017, 6:38 a.m.