Merge pull request #60 from yufongpeng/revert-59-release-0.7.2

Revert "Release 0.7.2"

src/fit.jl

@@ -50,28 +50,16 @@ end
 
 # Calculate dof from assign
 """
-    dof_asgn(assign::Vector{Int})
+    dof_asgn(v::Vector{Int})
 
-Calculate degrees of freedom of each predictors. 'assign' can be obtained by `StatsModels.asgn(f::FormulaTerm)`. For a given `trm::RegressionModel`, it is as same as `trm.mm.assign`.
-
-The index of the output matches values in the orinal `assign`. If any index value is not in `assign`, the default is 0.
-
-# Examples
-```julia
-julia> dof_asgn([1, 2, 2, 3, 3, 3])
-(1, 2, 3)
-
-julia> dof_asgn([2, 2, 3, 3, 3])
-(0, 2, 3)
-
-```
+Calculate degrees of freedom of each predictors. 'v' can be obtained by `StatsModels.asgn(f::FormulaTerm)`. For a given `trm::RegressionModel`, it is as same as `trm.mm.assign`.
 """
 function dof_asgn(v::Vector{Int})
     dofv = zeros(Int, maximum(v))
     for i in v
         @inbounds dofv[i] += 1
     end
-    tuple(dofv...)
+    dofv
 end
 
 @deprecate dof(v::Vector{Int}) dof_asgn(v::Vector{Int})

src/interface.jl

@@ -69,7 +69,7 @@ predictors(anovamodel::FullModel) = getindex.(Ref(predictors(anovamodel.model)),
     anovatable(aov::AnovaResult{<: NestedModels, LRT, N}; rownames = string.(1:N)) where N
 
 Return a table with coefficients and related statistics of ANOVA.
-When displaying `aov` in repl, `rownames` will be `prednames(aov)` for `FullModel` and `string.(1:N)` for `NestedModels`. 
+When displaying `aov` in repl, `rownames` will be `prednames(aov)` for `FullModel` and `"x" .* string.(1:N)` for `NestedModels`. 
 
 For nested models, there are two default methods for `FTest` and `LRT`; one can also define new methods dispatching on `::NestedModels{M}` where `M` is a model type. 
 
@@ -87,7 +87,7 @@ function anovatable(::AnovaResult{T, S, N}; rownames = "x" .* string.(1:N)) wher
 end
 
 # default anovatable api for comparing multiple models
-function anovatable(aov::AnovaResult{<: NestedModels, FTest, N}; rownames = string.(1:N)) where N
+function anovatable(aov::AnovaResult{<: NestedModels, FTest, N}; rownames = "x" .* string.(1:N)) where N
     AnovaTable([
                     dof(aov), 
                     [NaN, _diff(dof(aov))...], 
@@ -101,7 +101,7 @@ function anovatable(aov::AnovaResult{<: NestedModels, FTest, N}; rownames = stri
               rownames, 7, 6)
 end 
 
-function anovatable(aov::AnovaResult{<: NestedModels, LRT, N}; rownames = string.(1:N)) where N
+function anovatable(aov::AnovaResult{<: NestedModels, LRT, N}; rownames = "x" .* string.(1:N)) where N
     AnovaTable([
                     dof(aov), 
                     [NaN, _diff(dof(aov))...], 

test/runtests.jl

@@ -182,7 +182,7 @@ anovatable(::AnovaResult{<: FullModel{StatsModels.TableRegressionModel{Int64, Ma
         @test canonicalgoodnessoffit(Binomial()) == LRT
         @test AnovaBase.lrt_nested(NestedModels{StatsModels.TableRegressionModel}(model1, model1), (1,2), (1.5, 1.5), 0.1).teststat[2] == 0.0
         @test AnovaBase.ftest_nested(NestedModels{StatsModels.TableRegressionModel}((model1, model1)), (1,2), (10, 10), (1.5, 1.5), 0.1).teststat[2] == 0.0
-        @test dof_asgn([1, 2, 2, 2, 3]) == (1, 3, 1)
+        @test dof_asgn([1, 2, 2, 2, 3]) == [1, 3, 1]
     end
     global f = FormulaTerm(conterm, MatrixTerm((InterceptTerm{true}(), caterm(), fterm, InteractionTerm((caterm(), fterm)))))
     @testset "term.jl" begin