nsgpCovMatAsym: Calculate an asymmetric NSGP covariance matrix

In GPFDA: Gaussian Process for Functional Data Analysis

Calculate an asymmetric NSGP covariance matrix

Description

Calculate an asymmetric NSGP covariance matrix

Usage

nsgpCovMatAsym(
  hp,
  input,
  inputNew,
  nBasis = 5,
  corrModel = corrModel,
  gamma = NULL,
  nu = NULL,
  cyclic = NULL,
  whichTau = NULL
)

Arguments

hp	Vector of hyperparameters estimated by function nsgpr.
input	List of Q input variables (see Details).
inputNew	List of Q test set input variables.
nBasis	Number of B-spline basis functions in each coordinate direction along which parameters change.
corrModel	Correlation function specification used for g(.). It can be either "pow.ex" or "matern".
gamma	Power parameter used in powered exponential kernel function. It must be 0<gamma<=2.
nu	Smoothness parameter of the Matern class. It must be a positive value.
cyclic	Logical vector of dimension Q which defines which covariates are cyclic (periodic). For example, if basis functions should be cyclic only in the first coordinate direction, then cyclic=c(T,F). cyclic must have the same dimension of whichTau. If cyclic is TRUE for some coordinate direction, then cyclic B-spline functions will be used and the varying parameters (and their first two derivatives) will match at the boundaries of that coordinate direction.
whichTau	Logical vector of dimension Q identifying which input coordinates the parameters are function of. For example, if Q=2 and parameters change only with respect to the first coordinate, then we set whichTau=c(T,F).

Value

An asymmetric covariance matrix

References

Konzen, E., Shi, J. Q. and Wang, Z. (2020) "Modeling Function-Valued Processes with Nonseparable and/or Nonstationary Covariance Structure" <arXiv:1903.09981>.

GPFDA documentation built on Sept. 11, 2023, 1:08 a.m.