add tests for statsmodel functions

test/runtests.jl

@@ -25,7 +25,8 @@ my_tests = ["utils.jl",
             "join.jl",
             "iteration.jl",
             "duplicates.jl",
-            "show.jl"]
+            "show.jl",
+            "statsmodel.jl"]
 
 println("Running tests:")
 

test/statsmodel.jl

@@ -0,0 +1,52 @@
+module TestStatsModels
+using DataFrames
+using Base.Test
+
+# Tests for statsmodel.jl
+
+# A dummy RegressionModel type
+immutable DummyMod <: RegressionModel
+    x::Matrix
+    y::Vector
+end
+
+## dumb fit method: just copy the x and y input over
+StatsBase.fit(::Type{DummyMod}, x::Matrix, y::Vector) = DummyMod(x, y)
+## dumb coeftable: just prints the first four rows of the model (x) matrix
+StatsBase.coeftable(mod::DummyMod) =
+    CoefTable(transpose(mod.x),
+              ["row $n" for n in 1:min(4,size(mod.x,1))],
+              ["" for n in 1:size(mod.x,2)],
+              0)
+StatsBase.model_response(mod::DummyMod) = mod.y
+
+## Test fitting
+d = DataFrame()
+d[:y] = [1:4;]
+d[:x1] = [5:8;]
+d[:x2] = [9:12;]
+d[:x3] = [13:16;]
+d[:x4] = [17:20;]
+
+f = y ~ x1 * x2
+m = fit(DummyMod, f, d)
+@test model_response(m) == d[:y]
+
+## test prediction method
+## vanilla
+StatsBase.predict(mod::DummyMod) = mod.y
+@test predict(m) == d[:y]
+
+## new data from matrix
+StatsBase.predict(mod::DummyMod, newX::Matrix) = sum(mod.x, 2)
+mm = ModelMatrix(ModelFrame(f, d))
+@test predict(m, mm.m) == sum(mm.m, 2)
+
+## new data from DataFrame (via ModelMatrix)
+@test predict(m, d) == predict(m, mm.m)
+
+## test copying of names from Terms to CoefTable
+ct = coeftable(m)
+@test ct.rownms == ["(Intercept)", "x1", "x2", "x1 & x2"]
+
+end