wavelet.univariate: Univariate wavelet variance using furier transforms.
In forestgeo/ctfs: Tools for the Analysis of Forest Dynamics

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

Function to calculate the univariate wavelet variance using furier transforms.

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wavelet.univariate(raster = NULL, coords, gridsize = 2,
  plotdim = c(1000, 500), FUN = NULL, k0 = 8, dj = 0.15,
  graph = FALSE)

`raster`	Used if data is entered already as a raster matrix.
`coords`	An alternate to a raster table, a table with two (or three) columns giving coordinates x, y (and an optional mark) in that order. This is used to calculate a raster.
`gridsize`	Side of the square quadrate.
`plotdim`	The x and y dimensions of the plot.
`FUN`	Function to apply to the marked point pattern, by default it sums the values as would be used for sum of basal areas or sum of above graound biomass
`k0`	Numeric. Smoothing parameter of the wavelet filter. (k0 between 5.5-15), lower values of k0 produce a smoother wavelet variance.
`dj`	Numeric. Discretization of the scale axis.
`graph`	Logical. If TRUE plot the wavelet variace.

It accepts a raster data or a point pattern, which is the default if raster is not provided.

The wavelet variance describes the spatial autocorrelation or aggregation of tree distribution.

A wavelet variance greater than 1 indicates scales at which individuals are aggregated. A wavelet variance less than 1, indicates scales at which individuals are dis-aggregated. A wavelet variance equal to 1, indicates scales at which individuals are randomply distribuited (as Poisson process).

A graphical test is implemented on the null hypothesis of complete randomness.

If the wavelet variance is out of the conf bounds the tree distribution is significantly different from a random process.

Dependencies: needs the package 'spatstat'and the CTFSRpackage

A list containing vectors for the wavelet variance, the scale of the wavelet variance, the normalized variance, and the confidence intervals.

FUN If not specified (default) it counts points. E.g. can be used to sum the basal areas or above graound biomass.

Matteo Detto and Tania Brenes

wavelet.bivariate()

## Not run: 
rast1 = rasterize(,
  gridsize = 5,
  plotdim = c(100, 500),
  graph = TRUE)
wv = wavelet.univariate(
  coords = bciex::bci12t1mini[, c("gx", "gy")],
  k0 = 8,
  dj = 0.15,
  graph = TRUE
  )
# plots the scale of aggregation

## End(Not run)