cauchy: The generalized Cauchy correlation function

In GPBayes: Tools for Gaussian Process Modeling in Uncertainty Quantification

The generalized Cauchy correlation function

Description

This function computes the generalized Cauchy correlation function given a distance matrix. The generalized Cauchy covariance is given by

C(h) = \left\{ 1 + \left( \frac{h}{\phi} \right)^{\nu} \right\}^{-\alpha/\nu},

where \phi is the range parameter. \alpha is the tail decay parameter. \nu is the smoothness parameter. The case where \nu=2 corresponds to the Cauchy covariance model, which is infinitely differentiable.

Usage

cauchy(d, range, tail, nu)

Arguments

d	a matrix of distances
range	a numerical value containing the range parameter
tail	a numerical value containing the tail decay parameter
nu	a numerical value containing the smoothness parameter

Value

a numerical matrix

Author(s)

Pulong Ma [e-mail]

See Also

kernel

GPBayes documentation built on May 29, 2024, 7:30 a.m.