Description Usage Arguments Value Author(s) References See Also Examples
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.
1 |
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:: |
rand |
The type of randomization for significance computation (Erdös et.al, 2014):
|
n.rand |
The number of randomizations. |
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
.
Danilo Candido Vieira
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.
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