SMW: Split moving window analysis

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

View source: R/SMW.R

Description

Function SMW performs split moving window analysis (SMW) with randomizations tests. It may compute dissimilarities for a single window size or for several windows sizes.

Usage

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SMW(yo, ws, dist = "bray", rand = c("shift", "plot"), n.rand = 99)

Arguments

yo

The ordered community matrix.

ws

The window sizes to be analyzed. Either a single value or a vector of values.

dist

The dissimilarity index used in vegan::vegdist. Defaults to 'bray'.

rand

The type of randomization for significance computation (Erdös et.al, 2014):

  • "shift": restricted randomization in which data belonging to the same species are randomly shifted along the data series ("Random shift");

  • "plot": unrestricted randomization: each sample is randomly repositioned along the data series ("Random plot").

n.rand

The number of randomizations.

Value

A two-level list object (class smw) describing the SMW results for each window w analyzed. The smw object is of length ws, and each of the w slots is a list of SMW results:

Available methods for class "smw" are print, extract and plot.

Author(s)

Danilo Candido Vieira

References

See Also

plot.smw, extract.

Examples

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data(sim1)
sim1o<-OrdData(sim1$envi,sim1$comm)


ws20<-SMW(yo=sim1o$yo,ws=20)
pool<-SMW(yo=sim1o$yo,ws=c(20,30,40))

segRDA documentation built on July 31, 2019, 9:03 a.m.