nei.efdr: Find wavelet neighbourhood

Description Usage Arguments Value References Examples

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

1
nei.efdr(Z, wf = "la8", J = 2, b = 11, parallel = 1L)

Arguments

Z

image of size n1 by n2 where both n1,n2 have to be powers of two

wf

type of wavelet to employ. Please see waveslim::wave.filter for a full list of wavelet names

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

1
image <- matrix(rnorm(64),8,8)

EFDR documentation built on May 20, 2019, 9:02 a.m.