mgpCovMat: Calculate a multivariate Gaussian processes covariance matrix...

In GPFDA: Gaussian Process for Functional Data Analysis

Calculate a multivariate Gaussian processes covariance matrix given a vector of hyperparameters

Description

Calculate a multivariate Gaussian processes covariance matrix given a vector of hyperparameters

Usage

mgpCovMat(Data, hp)

Arguments

Data	List of two elements: 'input' and 'response'. The element 'input' is a list of N vectors, where each vector represents the input covariate values for a particular output. The element 'response' is the corresponding list of N matrices (if there are multiple realisations) or vectors (for a single realisation) representing the response variables.
hp	Vector of hyperparameters

Value

Covariance matrix

References

Shi, J. Q., and Choi, T. (2011), “Gaussian Process Regression Analysis for Functional Data”, CRC Press.

Examples

## See examples in vignette:
# vignette("mgpr", package = "GPFDA")

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