optimize_hyper_params: Optimize the hyper parameters of a GP

In ebenmichael/gaussianProcess: Fits Gaussian Processes for Regression

Description

Optimize the hyper parameters of a GP

Usage

optimize_hyper_params(X, y, kernel.type = rbf, order = 5/2, noise.var = 1,
  verbose = 0)

Arguments

X	An n x d matrix of covariates for observed data
y	An n dimensional vector of outputs for observed data
order	The order of the kernel, defaults to 5/2
noise.var	The variance of the noise around the function
verbose	Level of information printed out, defaults to 0
kernel	The covariance kernel of the process, defaults to rbf

Value

Hyper parameters which optimize the log marginal likelihood

ebenmichael/gaussianProcess documentation built on May 15, 2019, 7:30 p.m.