R: Gaussian Process for Functional Data Analysis

# Gaussian Process for Functional Data Analysis

## Documentation for package ‘GPFDA’ version 3.1.3

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

calcScaleDistMats | Calculate matrices for NSGP covariance function
cov.linear | Calculate a covariance matrix
cov.matern | Calculate a covariance matrix
cov.pow.ex | Calculate a covariance matrix
cov.rat.qu | Calculate a covariance matrix
covMat | Calculate a covariance matrix
D2 | Second derivative of the likelihood
dataExampleGPFR | Data simulated in the GPFR example
dataExampleMGPR | Data simulated in the MGPR example
distanceMatrix | Calculate generalised distances
distMat | Calculate generalised distances
distMatLinear | Calculate generalised distances
distMatLinearSq | Calculate generalised distances
distMatSq | Calculate generalised distances
gpfr | Gaussian process functional regression (GPFR) model
gpfrPredict | Prediction of GPFR model
gpr | Gaussian process regression (GPR) model
gprPredict | Prediction of GPR model
mat2fd | Create an 'fd' object from a matrix
mgpCovMat | Calculate a multivariate Gaussian processes covariance matrix given a vector of hyperparameters
mgpr | Multivariate Gaussian process regression (MGPR) model
mgprPredict | Prediction of MGPR model
nsgpCovMat | Calculate a NSGP covariance matrix given a vector of hyperparameters
nsgpCovMatAsym | Calculate an asymmetric NSGP covariance matrix
nsgpr | Estimation of a nonseparable and/or nonstationary covariance structure (NSGPR model)
nsgprPredict | Prediction of NSGPR model
plot.gpfr | Plot GPFR model for either training or prediction
plot.gpr | Plot GPR model for either training or prediction
plot.mgpr | Plot predictions of GPR model
plotImage | Draw an image plot for a given two-dimensional input
plotmgpCovFun | Plot auto- or cross-covariance function of a multivariate Gaussian process
unscaledCorr | Calculate an unscaled NSGP correlation matrix