kGauss

Gauss (or squared exponential) covariance function.

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.

Olivier Roustant

kergp

Gaussian Process Laboratory

kGauss function

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Arguments

Gauss (or squared exponential) covariance function.

Gauss (Squared-Exponential) Kernel — kGauss

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kGauss: Gauss (Squared-Exponential) Kernel

Description

Usage

Value

Arguments

References

Examples