nei.efdr {EFDR} | R Documentation |
Find wavelet neighbourhood
Description
Given an image, this function first computes the 2d DWT and then returns a
matrix of size N
by b
where N
is the number of wavelets and b
is the number of neighbours per wavelet. Two wavelets are deemed
to be neighbours according to the metric of Shen, Huang and Cressie (2002). The distance metric is a function of the
spatial separation, the resolution and the orientation.
Usage
nei.efdr(Z, wf = "la8", J = 2, b = 11, parallel = 1L)
Arguments
Z |
image of size |
wf |
type of wavelet to employ. Please see |
J |
number of resolutions to employ in the wavelet decomposition |
b |
number of neighbours to consider in EFDR |
parallel |
number of cores to use with parallel backend; needs to be an integer less than the number of available cores |
Value
matrix of size N
by b
References
Shen, X., Huang, H.-C., and Cressie, N. 'Nonparametric hypothesis testing for a spatial signal.' Journal of the American Statistical Association 97.460 (2002): 1122-1140.
Examples
image <- matrix(rnorm(64),8,8)