kappasb: Coefficients of an extended Shapiro-Botha variogram model

In rubenfcasal/npsp: Nonparametric Spatial Statistics

Coefficients of an extended Shapiro-Botha variogram model

Description

Computes the coefficients of an extended Shapiro-Botha variogram model.

Usage

kappasb(x, dk = 0)

Arguments

x	numeric vector (on which the kappa function will be evaluated).
dk	dimension of the kappa function.

Details

If dk >= 1, the coefficients are computed as:

\kappa_d(x) = (2/x)^{(d-2)/2} \Gamma(d/2) J_{(d-2)/2}(x)

where J_p is the Bessel function of order p.
If dk == 0, the coefficients are computed as:

\kappa _\infty(x) = e^{-x^2}

(corresponding to a model valid in any spatial dimension).
NOTE: some authors denote these functions as \Omega_d.

Value

A vector with the coefficients of an extended Shapiro-Botha variogram model.

References

Shapiro, A. and Botha, J.D. (1991) Variogram fitting with a general class of conditionally non-negative definite functions. Computational Statistics and Data Analysis, 11, 87-96.

See Also

svarmod.sb.iso, besselJ.

Examples

kappasb(seq(0, 6*pi, len = 10), 2)
  
curve(kappasb(x/5, 0), xlim = c(0, 6*pi), ylim = c(-1, 1), lty = 2)
for (i in 1:10) curve(kappasb(x, i), col = gray((i-1)/10), add = TRUE)
abline(h = 0, lty = 3)

rubenfcasal/npsp documentation built on April 23, 2023, 8:40 a.m.