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fixed cholesky error in simulate #314

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merged 4 commits into from
Aug 4, 2022
Merged

fixed cholesky error in simulate #314

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04c23a9
fixed cholesky error in simulate
dietzemarina Jul 29, 2022
52213d7
created cholesky_decomposition function
dietzemarina Aug 1, 2022
25f0ca3
increase rounding digits
dietzemarina Aug 2, 2022
2cfd9d8
updated version in Project.toml
dietzemarina Aug 4, 2022
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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name = "StateSpaceModels"
uuid = "99342f36-827c-5390-97c9-d7f9ee765c78"
authors = ["raphaelsaavedra <raphael.saavedra93@gmail.com>, guilhermebodin <guilherme.b.moraes@gmail.com>, mariohsouto"]
version = "0.6.4"
version = "0.6.5"

[deps]
Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
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2 changes: 1 addition & 1 deletion src/models/basicstructural_explanatory.jl
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Expand Up @@ -192,7 +192,7 @@ function simulate(
alpha = Matrix{Fl}(undef, n + 1, m)
# Sampling errors
chol_H = sqrt(sys.H[1])
chol_Q = cholesky(sys.Q[1])
chol_Q = cholesky_decomposition(sys.Q[1])
standard_ε = randn(n)
standard_η = randn(n + 1, size(sys.Q[1], 1))

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21 changes: 19 additions & 2 deletions src/systems.jl
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Expand Up @@ -312,6 +312,23 @@ function to_multivariate_time_variant(system::LinearUnivariateTimeVariant{Fl}) w
end

to_multivariate_time_variant(system::LinearMultivariateTimeVariant) = system
ispossemdef(M::Matrix{Fl}) where Fl = all(i -> i >= 0.0, eigvals(M))

function cholesky_decomposition(M::Matrix{Fl}) where Fl
if isposdef(M)
return cholesky(M)
elseif ispossemdef(M)
size_matrix = size(M, 1)
chol_M = cholesky(M .+ I(size_matrix) .* floatmin(Fl))
chol_M.L[:, :] = round.(chol_M.L; digits = 10)
chol_M.U[:, :] = round.(chol_M.U; digits = 10)
chol_M.UL[:, :] = round.(chol_M.UL; digits = 10)

return chol_M
else
@error("Matrix is not positive definite or semidefinite. Cholesky decomposition cannot be performed.")
end
end

# Functions for simulations
function simulate(
Expand All @@ -325,7 +342,7 @@ function simulate(
alpha = Matrix{Fl}(undef, n + 1, m)
# Sampling errors
chol_H = sqrt(sys.H)
chol_Q = cholesky(sys.Q)
chol_Q = cholesky_decomposition(sys.Q)
standard_ε = randn(n)
standard_η = randn(n + 2, size(sys.Q, 1))

Expand Down Expand Up @@ -357,7 +374,7 @@ function simulate(
alpha = Matrix{Fl}(undef, n + 1, m)
# Sampling errors
chol_H = cholesky(sys.H)
chol_Q = cholesky(sys.Q)
chol_Q = cholesky_decomposition(sys.Q)
standard_ε = randn(n, size(sys.H, 1))
standard_η = randn(n + 2, size(sys.Q, 1))

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