diff --git a/Project.toml b/Project.toml
index 49c19f0..96fdfbd 100644
--- a/Project.toml
+++ b/Project.toml
@@ -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 = "0.6.6"
+version = "0.6.7"
 
 [deps]
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
diff --git a/src/models/unobserved_components.jl b/src/models/unobserved_components.jl
index 262a522..36420e5 100644
--- a/src/models/unobserved_components.jl
+++ b/src/models/unobserved_components.jl
@@ -461,7 +461,7 @@ function initial_hyperparameters!(model::UnobservedComponents)
     if model.has_irregular
         initial_hyperparameters["sigma2_irregular"] = observed_variance
     end
-    if model.has_trend
+    if model.stochastic_trend
         initial_hyperparameters["sigma2_trend"] = observed_variance
     end
     if model.has_cycle
diff --git a/test/models/sarima.jl b/test/models/sarima.jl
index ee9c786..f1bbca7 100644
--- a/test/models/sarima.jl
+++ b/test/models/sarima.jl
@@ -29,7 +29,7 @@
     # Values are very close to 0.0 so we test with absolute tolerance
     # It attains 1e-3 when we make 10M simulations, which is too much
     # computation for a rather simple test.
-    test_scenarios_adequacy_with_forecast(forec, scenarios; atol=1e-1)
+    test_scenarios_adequacy_with_forecast(forec, scenarios; atol=2e-1)
 
     missing_obs = [6, 16, 26, 36, 46, 56, 66, 72, 73, 74, 75, 76, 86, 96]
     missing_dinternet = copy(dinternet)
diff --git a/test/models/unobserved_components.jl b/test/models/unobserved_components.jl
index f2c2192..0ce640e 100644
--- a/test/models/unobserved_components.jl
+++ b/test/models/unobserved_components.jl
@@ -40,4 +40,9 @@
     @test minimum(alpha[:, 1]) <= 296
     @test maximum(alpha[:, 2]) >= 7.5
     @test minimum(alpha[:, 2]) <= -7.5
+
+    # Testing that it does not break
+    rj_temp = CSV.File(StateSpaceModels.RJ_TEMPERATURE) |> DataFrame
+    model = UnobservedComponents(rj_temp.Values; trend = "smooth trend", cycle = "stochastic")
+    fit!(model)
 end
\ No newline at end of file