add test for IV

.travis.yml

@@ -1,14 +1,12 @@
 language: julia
 julia:
 - 0.7
+- 1.0
 - nightly
 matrix:
   allow_failures:
     - julia: nightly
-script:
-- if [[ -a .git/shallow ]]; then git fetch --unshallow; fi
-- julia --check-bounds=yes -e 'Pkg.clone(pwd()); Pkg.build("FixedEffectModels"); Pkg.test("FixedEffectModels"; coverage=true)'
 after_success:
-- julia -e 'cd(Pkg.dir("FixedEffectModels")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder())'
+- julia -e 'using Pkg; cd(Pkg.dir("FixedEffectModels")); Pkg.add("Coverage"); using Coverage; Coveralls.submit(Coveralls.process_folder())'
 notifications:
   email: false

REQUIRE

@@ -1,4 +1,4 @@
-julia 0.7.0-
+julia 0.7
 Distributions 0.4.6
 StatsBase 0.22.0
 StatsModels 0.2.4

src/RegressionResult.jl

@@ -249,13 +249,13 @@ end
 
 title(::RegressionResultIV) = "IV Model"
 top(x::RegressionResultIV) = [
-            "Number of obs" sprint(show, nobs(x), contect = :compact => true);
-            "Degrees of freedom" sprint(show, nobs(x) - df_residual(x), contect = :compact => true);
+            "Number of obs" sprint(show, nobs(x), context = :compact => true);
+            "Degrees of freedom" sprint(show, nobs(x) - df_residual(x), context = :compact => true);
             "R2" format_scientific(x.r2);
             "R2 Adjusted" format_scientific(x.r2_a);
-            "F-Statistic" sprint(show, x.F, contect = :compact => true);
+            "F-Statistic" sprint(show, x.F, context = :compact => true);
             "p-value" format_scientific(x.p);
-            "First Stage F-stat (KP)" sprint(show, x.F_kp, contect = :compact => true);
+            "First Stage F-stat (KP)" sprint(show, x.F_kp, context = :compact => true);
             "First Stage p-val (KP)" format_scientific(x.p_kp);
             ]
 

src/fixedeffect/FixedEffect.jl

@@ -113,7 +113,6 @@ function getindex(x::FixedEffect, idx)
     refs = x.refs[idx]
     sqrtw = x.sqrtw[idx]
     interaction = x.interaction[idx]
-
     scale = copy(x.scale)
     for i in 1:length(refs)
         scale[refs[i]] += abs2(interaction[i] * sqrtw[i])

test/RegressionResult.jl

@@ -15,6 +15,7 @@ residuals(result, df)
 
 model = @model Sales ~ CPI + (Price ~ Pimin)
 result = reg(df, model)
+show(result)
 predict(result, df)
 residuals(result, df)
 model_response(result, df)