Add missing methods for isnested for Table(Statistical|Regression)Model (#245)

* add isnested method for TableRegressionModel

* also statistical model

* bugfix bump patch

* add test, one method

Author: kleinschmidt

Project.toml

@@ -1,6 +1,6 @@
 name = "StatsModels"
 uuid = "3eaba693-59b7-5ba5-a881-562e759f1c8d"
-version = "0.6.26"
+version = "0.6.27"
 
 [deps]
 DataAPI = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a"

src/lrtest.jl

@@ -50,8 +50,6 @@ julia> model = glm(@formula(Result ~ 1 + Treatment), dat, Binomial(), LogitLink(
 julia> bigmodel = glm(@formula(Result ~ 1 + Treatment + Other), dat, Binomial(), LogitLink());
 
 julia> lrtest(nullmodel, model, bigmodel)
-┌ Warning: Could not check whether models are nested as model type TableRegressionModel does not implement isnested: results may not be meaningful
-└ @ StatsModels ~/.julia/dev/StatsModels/src/lrtest.jl:108
 Likelihood-ratio test: 3 models fitted on 12 observations
 ──────────────────────────────────────────────
      DOF  ΔDOF  Deviance  ΔDeviance  p(>Chisq)
@@ -62,8 +60,6 @@ Likelihood-ratio test: 3 models fitted on 12 observations
 ──────────────────────────────────────────────
 
 julia> lrtest(bigmodel, model, nullmodel)
-┌ Warning: Could not check whether models are nested as model type TableRegressionModel does not implement isnested: results may not be meaningful
-└ @ StatsModels ~/.julia/dev/StatsModels/src/lrtest.jl:108
 Likelihood-ratio test: 3 models fitted on 12 observations
 ──────────────────────────────────────────────
      DOF  ΔDOF  Deviance  ΔDeviance  p(>Chisq)

src/statsmodel.jl

@@ -144,6 +144,8 @@ StatsBase.r2(mm::TableRegressionModel, variant::Symbol) = r2(mm.model, variant)
 StatsBase.adjr2(mm::TableRegressionModel, variant::Symbol) = adjr2(mm.model, variant)
 StatsBase.loglikelihood(mm::TableModels, c::Colon) = loglikelihood(mm.model, c)
 
+isnested(m1::TableModels, m2::TableModels; kwargs...) = isnested(m1.model, m2.model; kwargs...)
+
 function _return_predictions(T, yp::AbstractVector, nonmissings, len)
     out = Vector{Union{eltype(yp),Missing}}(missing, len)
     out[nonmissings] = yp

test/statsmodel.jl

@@ -106,6 +106,7 @@ end
 StatsBase.fit(::Type{DummyModTwo}, ::Matrix, ::Vector) = DummyModTwo("hello!")
 Base.show(io::IO, m::DummyModTwo) = println(io, m.msg)
 
+
 @testset "stat model types" begin
 
     ## Test fitting
@@ -264,6 +265,19 @@ end
         [2]    2     1    3.2600   -10.7400     0.0010
         ──────────────────────────────────────────────"""
 
+    @testset "isnested with TableRegressionModel" begin
+        d = DataFrame(y=y, x1=x1, x2=x2)
+
+        m0 = fit(DummyMod, @formula(y ~ 1), d)
+        m1 = fit(DummyMod, @formula(y ~ 1 + x1), d)
+        m2 = fit(DummyMod, @formula(y ~ 1 + x1 * x2), d)
+
+        @test StatsModels.isnested(m0, m1)
+        @test StatsModels.isnested(m1, m2)
+        @test StatsModels.isnested(m0, m2)
+    end
+    
+
     m0 = DummyModNoIntercept(Float64[], ones(4, 0), y)
     m1 = DummyModNoIntercept([0.3], reshape(x1, :, 1), y)
     m2 = DummyModNoIntercept([0.25, 0.05, 0.04], [x1 x2 x1.*x2], y)