fix explanatory

Author: guilhermebodin

Project.toml

@@ -1,7 +1,7 @@
 name = "StateSpaceModels"
 uuid = "99342f36-827c-5390-97c9-d7f9ee765c78"
 authors = ["raphaelsaavedra <[email protected]>, guilhermebodin <[email protected]>, mariohsouto"]
-version = "0.5.14"
+version = "0.5.15"
 
 [deps]
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"

src/models/basicstructural_explanatory.jl

@@ -69,9 +69,8 @@ function default_filter(model::BasicStructuralExplanatory)
     Fl = typeof_model_elements(model)
     steadystate_tol = Fl(1e-5)
     a1 = zeros(Fl, num_states(model))
-    P1 = zeros(Fl, num_states(model), num_states(model))
-    P1[1:13, 1:13] = Fl(1e6) .* Matrix{Fl}(I, 13, 13)
-    return UnivariateKalmanFilter(a1, P1, 13, steadystate_tol)
+    P1 = Fl(1e6) .* Matrix{Fl}(I, num_states(model), num_states(model))
+    return UnivariateKalmanFilter(a1, P1, num_states(model), steadystate_tol)
 end
 
 function initial_hyperparameters!(model::BasicStructuralExplanatory)
@@ -127,14 +126,6 @@ function fill_model_system!(model::BasicStructuralExplanatory)
     return model
 end
 
-function fill_model_filter!(filter::KalmanFilter, model::BasicStructuralExplanatory)
-    for i in axes(model.exogenous, 2)
-        filter.kalman_state.a[i + 13] = get_constrained_value(model, get_beta_name(model, i))
-    end
-    return filter
-end
-
-
 function fill_H_in_time(model::BasicStructuralExplanatory, H::Fl) where Fl
     return fill_system_matrice_with_value_in_time(model.system.H, H)
 end

src/models/locallevelexplanatory.jl

@@ -57,9 +57,7 @@ end
 function default_filter(model::LocalLevelExplanatory)
     Fl = typeof_model_elements(model)
     a1 = zeros(Fl, num_states(model)) 
-    # P1 is identity on sigma \eta and 0 otherwise.
-    P1 = zeros(Fl, num_states(model), num_states(model))
-    P1[1] = Fl(1e6)
+    P1 = Fl(1e6) .* Matrix{Fl}(I, num_states(model), num_states(model))
     steadystate_tol = Fl(1e-5)
     return UnivariateKalmanFilter(a1, P1, num_states(model), steadystate_tol)
 end
@@ -110,13 +108,6 @@ function fill_model_system!(model::LocalLevelExplanatory)
     return model
 end
 
-function fill_model_filter!(filter::KalmanFilter, model::LocalLevelExplanatory)
-    for i in axes(model.exogenous, 2)
-        filter.kalman_state.a[i + 1] = get_constrained_value(model, get_beta_name(model, i))
-    end
-    return filter
-end
-
 function fill_H_in_time(model::LocalLevelExplanatory, H::Fl) where Fl
     return fill_system_matrice_with_value_in_time(model.system.H, H)
 end

test/models/basicstructural_explanatory.jl

@@ -10,11 +10,8 @@
     # For a fixed forecasting explanatory the variance must not decrease
     forec = forecast(model, ones(10, 2))
     @test monotone_forecast_variance(forec)
-    kf = kalman_filter(model);
-    ks = kalman_smoother(model);
-    a = get_predictive_state(kf)
-    @test a[1, 14] ≈ a[end, 14] atol=1e-3
-    @test a[1, 15] ≈ a[end, 15] atol=1e-3
+    kf = kalman_filter(model)
+    ks = kalman_smoother(model)
     @test_throws AssertionError simulate_scenarios(model, 10, 1000, ones(5, 2))
     scenarios = simulate_scenarios(model, 10, 1000, ones(10, 2))
     test_scenarios_adequacy_with_forecast(forec, scenarios)

test/models/locallevelexplanatory.jl

@@ -43,7 +43,4 @@
     @test monotone_forecast_variance(forec)
     kf = kalman_filter(model)
     ks = kalman_smoother(model)
-    a = get_predictive_state(kf)
-    @test a[1, 2] ≈ a[end, 2] atol=1e-3
-    @test a[1, 3] ≈ a[end, 3] atol=1e-3
 end