From fd6c75322504529825ab075b0300e6d323a258a7 Mon Sep 17 00:00:00 2001 From: matthieugomez Date: Tue, 31 Mar 2020 10:49:15 -0400 Subject: [PATCH] Update runtests.jl --- test/runtests.jl | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/test/runtests.jl b/test/runtests.jl index afc4424..9254449 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -3,7 +3,7 @@ using InfinitesimalGenerators, Test, Statistics, LinearAlgebra, Expokit xbar = 0.0 κ = 0.1 σ = 0.02 -X = InfinitesimalGenerators.OrnsteinUhlenbeck(; xbar = xbar, κ = κ, σ = σ, length = 1000) +X = OrnsteinUhlenbeck(; xbar = xbar, κ = κ, σ = σ, length = 1000) ## Feynman-Kac @@ -81,7 +81,7 @@ l, η, r = cgf(m; eigenvector = :both)(ζ) # Test that the modified process μ + σ^2 ∂ ln(r) has a stationary distribution given by $r^2ψ$ -X = InfinitesimalGenerators.OrnsteinUhlenbeck(;κ =κ, σ = σ, length = 1000) +X = OrnsteinUhlenbeck(;κ =κ, σ = σ, length = 1000) m = AdditiveFunctionalDiffusion(X, μm .+ X.x .- 0.02, σm .* ones(length(X.x))) ψ = stationary_distribution(X) ζ = tail_index(m) @@ -101,7 +101,7 @@ l, η, r = cgf(m; eigenvector = :both)(ζ) # Test CIR gbar = 0.03 σ = 0.01 -X = InfinitesimalGenerators.CoxIngersollRoss(xbar = gbar, κ = κ, σ = σ) +X = CoxIngersollRoss(xbar = gbar, κ = κ, σ = σ) m = AdditiveFunctionalDiffusion(X, X.x, zeros(length(X.x))) η_analytic = gbar * κ^2 / σ^2 * (1 - sqrt(1 - 2 * σ^2 / κ^2)) @test cgf(m)(1.0)[2] ≈ η_analytic rtol = 1e-2