Gaussian Process for Functional Data Analysis


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Documentation for package ‘GPFDA’ version 3.1.3

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