scalogram | R Documentation |
The function decomposes the variance of a variable x
on a basis of
orthogonal vectors. The significance of the associated R-squared values is
tested by a randomization procedure. A smoothed scalogram is obtained by
summing the R-squared values into nblocks
.
scalogram(
x,
orthobasisSp,
nblocks = ncol(orthobasisSp),
nrepet = 999,
p.adjust.method = "none"
)
## S3 method for class 'scalogram'
plot(x, pos = -1, plot = TRUE, ...)
x |
a numeric vector for univariate data or an object of class |
orthobasisSp |
an object of class |
nblocks |
an integer indicating the number of blocks in the smoothed scalogram |
nrepet |
an integer indicating the number of permutations used in the randomization procedure |
p.adjust.method |
a string indicating a method for multiple adjustment,
see |
pos |
an integer indicating the position of the environment where the
data are stored, relative to the environment where the function is called.
Useful only if |
plot |
a logical indicating if the graphics is displayed |
... |
additional graphical parameters (see |
On the plot, oberved R-squared values are represent by bars. A black line indicate the 0.95 quantile of the values obtained by permutations. Significant values are indicated by a '*'
The function scalogram
returns an object of class
scalogram
, subclass krandtest
. The plot
function
returns an object of class ADEgS
, generated by the functions of the
adegraphics
package
Stéphane Dray stephane.dray@univ-lyon1.fr
Dray S., Pélissier R., Couteron P., Fortin M.J., Legendre P., Peres-Neto P.R., Bellier E., Bivand R., Blanchet F.G., De Caceres M., Dufour A.B., Heegaard E., Jombart T., Munoz F., Oksanen J., Thioulouse J., Wagner H.H. (2012). Community ecology in the age of multivariate multiscale spatial analysis. Ecological Monographs 82, 257–275.
mem
orthobasis
if(require("ade4", quietly = TRUE) & require("spdep", quietly = TRUE)){
data(mafragh)
me <- mem(nb2listw(mafragh$nb))
if(require("adegraphics", quietly = TRUE)){
sc1 <- scalogram(mafragh$env$Conduc, me, nblocks = 10)
plot(sc1)
}
}
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