kergp (version 0.5.7)

Gaussian Process Laboratory

Description

Gaussian process regression with an emphasis on kernels. Quantitative and qualitative inputs are accepted. Some pre-defined kernels are available, such as radial or tensor-sum for quantitative inputs, and compound symmetry, low rank, group kernel for qualitative inputs. The user can define new kernels and composite kernels through a formula mechanism. Useful methods include parameter estimation by maximum likelihood, simulation, prediction and leave-one-out validation.

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Install

install.packages('kergp')

Monthly Downloads

367

Version

0.5.7

License

GPL-3

Last Published

February 5th, 2024

Functions in kergp (0.5.7)