# The Gaussian Process Model

Below I will describe the essential components of the Gaussian Process (GP) Model, designed by Dr. Pritam Ranjan at Acadia University. You will quickly begin to see why efficient and robust optimization of the Model’s processes (particularly through the maximum

# Optimization of the GP Model

The negative log-likelihood, is dependent upon several components, namely the mean and variance estimators and $\hat{\sigma}^2(\beta)$, as well as the inverse and determinant of , all of which are dependent upon the hyper-parameter . Recall that each is a vector