DiracKernel
The Dirac kernel with conditional mean prameter $\mu$ is denotd by
\[k(y\mid x) = \delta(y - \mu(x)).\]
Types
MarkovKernels.AbstractDiracKernel — TypeAbstractDiracKernelAbstract type for representing Dirac kernels.
MarkovKernels.DiracKernel — TypeDiracKernelType for representing Dirac kernels K(y,x) = δ(y - μ(x)).
MarkovKernels.IdentityKernel — TypeIdentityKernelStruct for representing kernels that act like identity under marginalization.
Type aliases
const AffineDiracKernel{T} = DiracKernel{T,<:AbstractAffineMap}Methods
Statistics.mean — Methodmean(K::AbstractDiracKernel)Computes the conditonal mean function of the Dirac kernel K. That is, the output is callable.
Base.rand — Methodrand([rng::AbstractRNG], K::AbstractDiracKernel, x::AbstractVector)Computes a random vector conditionally on x with respect the the Dirac kernel K using the random number generator RNG. Equivalent to mean(K)(x).