wlmtest: Statistical comparison of wavelet linear models
In wsyn: Wavelet Approaches to Studies of Synchrony in Ecology and Other Fields

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

Compares a wavelet linear model with a nested model. Also the generator function for the wlmtest class.

1	wlmtest(wlmobj, drop, sigmethod, nrand = 1000)

`wlmobj`	A `wlm` object
`drop`	Either names or indices of variables in `wlmobj$dat` that are being dropped to form the simpler, nested model. The first variable in `wlmobj$dat`, which is the response, is not allowed here.
`sigmethod`	Method for significance testing. One of "`fft`", "`aaft`", "`fast`". See details.
`nrand`	The number of randomizations to do for significance

The slot signif provides the core information on significance. If sigmethod is not "fast", then signif$coher is the same as wlmobj$coher, and signif$scoher is a matrix of dimensions nrand by length(signif$coher) with rows equal to coherences between refitted models and the response-variable transforms, for datasets where the variables specified in drop have been replaced by surrogates. Normalization as specified in norm is used. The type of surrogate used (Fourier surrogates or amplitude adjusted Fourier surrogates, see surrog) is determined by sigmethod ("fft" or "aaft"). Synchrony-preserving surrogates are used. A variety of statements of significance (or lack thereof) can be made by comparing signif$coher with signif$scoher (see the plotmag, plotrank, and bandtest methods for the wlmtest class). If sigmethod is "fast", a fast algorithm of Lawrence Sheppard is used which is a generalization to wavelet linear models of the fast algorithm for coherence described in Sheppard et al (2017). In that case signif$coher can be compared to signif$scoher to make significance statements about the coherence in exactly the same way, but signif$coher will no longer precisely equal wlmobj$coher, and wlmobj$coher should not be compared directly to signif$scoher. Statements about significance of the coherence should be made using signif$coher and signif$scoher, whereas wlmobj$coher should be used whenever the actual value of the coherence is needed.

The slots ranks and bandp are empty on an initial call to wlmtest. They are made to compute and hold aggregate significance results over any timescale band of choice. These are filled in when needed by other methods, see plotrank and bandtest.

wlmtest returns an object of class wlmtest. Slots are:

`wlmobj`	The input
`drop`	The input
`signif`	A list with information from the significance testing. Elements are `sigmethod` (the input), `coher` and `scoher`. See details.
`ranks`	A list with ranking information for `signif`. `NA` until `plotrank` or `bandtest` is called.
`bandp`	A data frame containing results of computing significances across timescale bands. Empty on an initial call to `wlmtest`, filled in by the function `bandtest`. See details.

Thomas Anderson, anderstl@gmail.com, Jon Walter, jaw3es@virginia.edu; Lawrence Sheppard, lwsheppard@ku.edu; Daniel Reuman, reuman@ku.edu

Sheppard, L.W., et al. (2016) Changes in large-scale climate alter spatial synchrony of aphid pests. Nature Climate Change. DOI: 10.1038/nclimate2881

Sheppard, L.W., et al. (2017) Rapid surrogate testing of wavelet coherences. European Physical Journal, Nonlinear and Biomedical Physics, 5, 1. DOI: 10.1051/epjnbp/2017000

Sheppard, LW et al. (2019) Synchrony is more than its top-down and climatic parts: interacting Moran effects on phytoplankton in British seas. Plos Computational Biology 15, e1006744. doi: 10.1371/journal.pcbi.1006744

wlm, plotrank, bandtest, coh, wlmtest_methods, browseVignettes("wsyn")

times<-1:30
dat<-list(v1=matrix(rnorm(300),10,30),v2=matrix(rnorm(300),10,30),v3=matrix(rnorm(300),10,30),
          v4=matrix(rnorm(300),10,30),v5=matrix(rnorm(300),10,30))
dat<-lapply(FUN=function(x){cleandat(x,times,1)$cdat},X=dat)
resp<-1
pred<-2:3
norm<-"powall"
wlmobj<-wlm(dat,times,resp,pred,norm)
drop<-3
sigmethod<-"fft"
res<-wlmtest(wlmobj,drop,sigmethod,nrand=10)