Man pages for mattdneal/gaussianProcess
Gaussian Process Fitting and Prediction

add.kernelAdd a Kernel Class to a Model Tree
as.character.ModelTreeConvert a Model Tree to a String
bayesian.information.criterionCalculate BIC of a GP
bayesian.information.criterion.EDoFCalculate BIC of a GP (Effective DoF)
bayesian.information.criterion.EDoF.eigenCalculate BIC of a GP (Effective DoF, eigenvalue...
bootifyBootify a Statistic
callKernelByStringSelect Built-in C++ Kernels by Name
create.ard.kernelCreate an ARD kernel object
create.gaussian.processCreate a gaussianProcess object
create.kernel.objectCreate a kernel object
create.kernel.object.from.model.treeCreate Kernel object from model tree
create.model.treeCreate an Empty Model Tree
create.model.tree.builtinCreate a Model Tree Containing All Built-in Kernels
create.model.tree.builtin.scaledCreate a Model Tree Containing All Built-in Kernels (scaled)
create.model.tree.from.listCreate a Model Tree from a list of kernel objects
create.numeric.gradCreate a numerical gradient function for a kernel using the...
create.numeric.hessianCreate a numerical Hessian function for a kernel using the...
create.numeric.hessian.from.gradCreate a numerical Hessian function from a kernel grad using...
create.rf.additional.paramsCreate Additional Params List for Random Forest Kernel
delete.nodeDelete a Node in a Model Tree
eval.cov.mat.grad.nodeEvaluate Covariance Matrix Grad of a Model Tree Node
eval.cov.mat.hess.nodeEvaluate Covariance Matrix Hessian of a Model Tree Node
eval.cov.mat.nodeEvaluate Covariance Matrix of a Model Tree Node
eval.node.kstar.matK* matrix of a model tree node
fit.hyperparamsFit hyperparameters for a GP using maximum likelihood...
gaussianProcess-packageUtilities for training Gaussian processes.
get.alphaGet alpha for a GP
get_covariance_matrixGet the Covariance Matrix for a Kernel
get_covariance_matrix.characterGet the Covariance Matrix for a built-in kernel
get_covariance_matrix.functionGet the Covariance Matrix for a kernel function
get_covariance_matrix_grad.characterGet the Covariance Matrix grad for a built-in kernel
get_covariance_matrix_grad.functionGet the Covariance Matrix grad for a kernel function
get_covariance_matrix_grad.KernelGet the Covariance Matrix Grad for a Kernel
get_covariance_matrix_grad.ModelTreeGet the Covariance Matrix Grad for a Kernel ModelTree
get_covariance_matrix_hess.characterGet the Covariance Matrix Hessian for a built-in kernel
get_covariance_matrix_hess.functionGet the Covariance Matrix Hessian for a kernel function
get_covariance_matrix_hess.KernelGet the Covariance Matrix Hessian for a Kernel
get_covariance_matrix_hess.ModelTreeGet the Covariance Matrix Hessian for a Kernel ModelTree
get_covariance_matrix.KernelGet the Covariance Matrix for a Kernel
get_covariance_matrix.ModelTreeGet the Covariance Matrix for a Kernel ModelTree
get.cov.mat.cholGet the Cholesky decomposition of a covariance matrix
get.inst.cov.matsGet Kernel Instance Covariance Matrices, Grads or Hessians
get_kstar_matrixGet predictive K* matrix
get_kstar_matrix.characterGet predictive K* matrix
get_kstar_matrix.functionGet predictive K* matrix
get_kstar_matrix.KernelGet predictive K* matrix
get_kstar_matrix.ModelTreeK* Matrix of a Model Tree
get.marginal.likelihoodGet Log Marginal Likelihood of a GP
get.marginal.likelihood.gradGet the Grad of the Log Marginal Likelihood of a GP
get.marginal.likelihood.hessianGet the Hessian of the Log Marginal Likelihood of a GP
get.normal.priorReturn an object representing a normal prior over...
get.uniform.priorReturn an object representing a uniform prior over...
insert.kernel.instanceInsert Kernel Instance into Model Tree
list_built_in_kernelsReturn a list containing built in kernels.
list_built_in_kernels_scaledReturn a list of built-in kernels scaled with a constant...
list_polynomial_kernelsCreate a list of polynomial kernels
model.searchPerform Model Selection Using BIC
plot.GaussianProcessPlot a Gaussian Process
posterior.laplace.approximationCalculate Laplace Approximation of a GP
predict.GaussianProcessCreate Predictions Using a Gaussian Process
print.KernelPrint a kernel
random.forest.partition.function.generatorRandom forest kernel
random.partition.kernelRandom Partition Kernel
rmseRegression fit metrics
sample.functions.from.kernelSample a function from a Gaussian Process Prior
scale_kernelScale a kernel
scale_kernel_listScale a list of kernel objects
summary.ModelTreePrint a Summary of a Model Tree
test.kernel.gradTest an Analytic Gradient Against a Numeric Gradient
test.structure.recreationTest the ability of the BIC search to identify the data...
mattdneal/gaussianProcess documentation built on May 21, 2017, 9:56 p.m.