Ensemble Kalman Sampler
EnsembleKalmanProcesses.Sampler
— TypeSampler{FT<:AbstractFloat,IT<:Int} <: Process
An ensemble Kalman Sampler process.
Fields
prior_mean::Vector{FT} where FT<:AbstractFloat
Mean of Gaussian parameter prior in unconstrained space
prior_cov::Union{LinearAlgebra.UniformScaling{FT}, AbstractMatrix{FT}} where FT<:AbstractFloat
Covariance of Gaussian parameter prior in unconstrained space
Constructors
Sampler(prior_mean, prior_cov)
defined at /home/runner/work/EnsembleKalmanProcesses.jl/EnsembleKalmanProcesses.jl/src/EnsembleKalmanSampler.jl:17
.
Sampler(prior)
defined at /home/runner/work/EnsembleKalmanProcesses.jl/EnsembleKalmanProcesses.jl/src/EnsembleKalmanSampler.jl:23
.
EnsembleKalmanProcesses.eks_update
— Function eks_update(
ekp::EnsembleKalmanProcess{FT, IT, Sampler{FT}},
u::AbstractMatrix{FT},
g::AbstractMatrix{FT},
) where {FT <: Real, IT}
Returns the updated parameter vectors given their current values and the corresponding forward model evaluations, using the sampler algorithm.
The current implementation assumes that rows of u and g correspond to ensemble members, so it requires passing the transpose of the u
and g
arrays associated with ekp.