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Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: Maximilian-Stefan-Ernst

ext/SEMProximalOptExt/ProximalAlgorithms.jl

@@ -93,9 +93,7 @@ SEM.algorithm_name(
 SEM.convergence(
     ::ProximalResult,
 ) = "No standard convergence criteria for proximal \n algorithms available."
-SEM.converged(
-    ::ProximalResult,
-) = missing
+SEM.converged(::ProximalResult) = missing
 SEM.n_iterations(res::ProximalResult) = res.n_iterations
 
 ############################################################################################

src/frontend/fit/standard_errors/bootstrap.jl

@@ -48,7 +48,7 @@ function bootstrap(
     engine = :Optim,
     parallel = false,
     fit_kwargs = Dict(),
-    replace_kwargs = Dict()
+    replace_kwargs = Dict(),
 )
     # access data and convert to matrix
     data = prepare_data_bootstrap(data, fitted.model)
@@ -121,7 +121,8 @@ function bootstrap(
         :n_boot => n_boot,
         :n_converged => sum(conv),
         :converged => conv,
-        :n_errored => n_failed[])
+        :n_errored => n_failed[],
+    )
 end
 
 """
@@ -171,7 +172,7 @@ function se_bootstrap(
     engine = :Optim,
     parallel = false,
     fit_kwargs = Dict(),
-    replace_kwargs = Dict()
+    replace_kwargs = Dict(),
 )
     # access data and convert to matrix
     data = prepare_data_bootstrap(data, fitted.model)
@@ -196,7 +197,7 @@ function se_bootstrap(
                 sol = solution(new_fit)
                 conv = converged(new_fit)
                 if conv
-                    n_conv[] += 1
+                    n_conv[]             += 1
                     @. total_sum         += sol
                     @. total_squared_sum += sol^2
                 end
@@ -228,7 +229,7 @@ function se_bootstrap(
                 conv = converged(new_fit)
                 if conv
                     lock(lk) do
-                        n_conv[] += 1
+                        n_conv[]             += 1
                         @. total_sum         += sol
                         @. total_squared_sum += sol^2
                     end

src/frontend/fit/standard_errors/confidence_intervals.jl

@@ -21,23 +21,22 @@ Return normal-theory confidence intervals for all model parameters.
 """
 
 @doc "$(_doc_normal_CI)"
-function normal_CI(
-        fitted, se; α = 0.05, name_lower = :ci_lower, name_upper = :ci_upper)
+function normal_CI(fitted, se; α = 0.05, name_lower = :ci_lower, name_upper = :ci_upper)
     qnt = quantile(Normal(0, 1), 1-α/2);
     sol = solution(fitted)
     return Dict(name_lower => sol - qnt*se, name_upper => sol + qnt*se)
 end
 
 @doc "$(_doc_normal_CI)"
 function normal_CI!(
-        partable,
-        fitted,
-        se;
-        α = 0.05,
-        name_lower = :ci_lower,
-        name_upper = :ci_upper)
-    cis = normal_CI(
-        fitted, se; α, name_lower, name_upper)
+    partable,
+    fitted,
+    se;
+    α = 0.05,
+    name_lower = :ci_lower,
+    name_upper = :ci_upper,
+)
+    cis = normal_CI(fitted, se; α, name_lower, name_upper)
     update_partable!(partable, name_lower, fitted, cis[name_lower])
     update_partable!(partable, name_upper, fitted, cis[name_upper])
     return cis

src/frontend/fit/standard_errors/z_test.jl

@@ -22,7 +22,7 @@ Tests the null hypothesis that each parameter is zero using the test statistic
 
 @doc "$(_doc_z_test)"
 function z_test(fitted, se)
-    dev = solution(fitted)./se
+    dev = solution(fitted) ./ se
     dist = Normal(0, 1)
     p = 2*ccdf.(dist, abs.(dev))
     return p

test/examples/helper.jl

@@ -153,4 +153,4 @@ function smoketest_CI_z(model_fit, partable)
     se_he = se_hessian(model_fit)
     normal_CI!(partable, model_fit, se_he)
     z_test!(partable, model_fit, se_he)
-end
+end