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.
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.
Returns
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:
..$dp: The raw dissimilarity profile (DP). The DP is a data frame giving the positions, labels, values of dissimilarity and z-scores for each sample;
..$rdp: data frame containing the randomized DP;
..$md: mean dissimilarity of the randomized DP;
..$sd: standard deviation for each sample position;
..$oem: overall expected mean dissimilarity;
..$osd: average standard deviation for the dissimilarities;
..$params: list with input arguments
Available methods for class "smw" are print, extract and plot.
Erdos, L., Z. Bátori, C. S. Tölgyesi, and L. Körmöczi. 2014. The moving split window (MSW) analysis in vegetation science - An overview. Applied Ecology and Environmental Research 12:787–805.
Cornelius, J. M., and J. F. Reynolds. 1991. On Determining the Statistical Significance of Discontinuities with Ordered Ecological Data. Ecology 72:2057–2070.