Change argument name vcov to vce

Author: junyuan-chen

src/InteractionWeightedDIDs.jl

@@ -24,9 +24,6 @@ import DiffinDiffsBase: required, default, transformed, combinedargs, _getsubcol
     valid_didargs, result
 import FixedEffectModels: has_fe
 
-# Handle naming conflicts
-const getvcov = vcov
-
 export Vcov,
        fe
 

src/procedures.jl

@@ -1,27 +1,27 @@
 """
     checkvcov!(args...)
 
-Exclude rows that are invalid for `vcov`.
+Exclude rows that are invalid for variance-covariance estimator.
 See also [`CheckVcov`](@ref).
 """
 checkvcov!(data, esample::BitVector,
-    vcov::Union{Vcov.SimpleCovariance, Vcov.RobustCovariance}) = NamedTuple(), false
+    vce::Union{Vcov.SimpleCovariance, Vcov.RobustCovariance}) = NamedTuple(), false
 
-function checkvcov!(data, esample::BitVector, vcov::Vcov.ClusterCovariance)
-    esample .&= Vcov.completecases(data, vcov)
+function checkvcov!(data, esample::BitVector, vce::Vcov.ClusterCovariance)
+    esample .&= Vcov.completecases(data, vce)
     return (esample=esample,), false
 end
 
 """
     CheckVcov <: StatsStep
 
-Call [`InteractionWeightedDIDs.checkvcov!`](@ref) to exclude invalid rows for
-`Vcov.CovarianceEstimator`.
+Call [`InteractionWeightedDIDs.checkvcov!`](@ref) to
+exclude rows that are invalid for variance-covariance estimator.
 """
 const CheckVcov = StatsStep{:CheckVcov, typeof(checkvcov!)}
 
 required(::CheckVcov) = (:data, :esample)
-default(::CheckVcov) = (vcov=Vcov.robust(),)
+default(::CheckVcov) = (vce=Vcov.robust(),)
 
 """
     checkfes!(args...)
@@ -336,24 +336,24 @@ const SolveLeastSquares = StatsStep{:SolveLeastSquares, typeof(solveleastsquares
 required(::SolveLeastSquares) = (:tr, :yterm, :xterms, :yxterms, :yxcols, :treatcols,
     :has_fe_intercept)
 
-function _vcov(data, esample::BitVector,
-        vcov::Union{Vcov.SimpleCovariance,Vcov.RobustCovariance}, fes::Vector{FixedEffect})
+function _vce(data, esample::BitVector,
+        vce::Union{Vcov.SimpleCovariance,Vcov.RobustCovariance}, fes::Vector{FixedEffect})
     dof_absorb = 0
     for fe in fes
         dof_absorb += nunique(fe)
     end
-    return vcov, dof_absorb
+    return vce, dof_absorb
 end
 
-function _vcov(data, esample::BitVector, vcov::Vcov.ClusterCovariance,
+function _vce(data, esample::BitVector, vce::Vcov.ClusterCovariance,
         fes::Vector{FixedEffect})
-    cludata = _getsubcolumns(data, vcov.clusters, esample)
-    concrete_vcov = Vcov.materialize(cludata, vcov)
+    cludata = _getsubcolumns(data, vce.clusters, esample)
+    concrete_vce = Vcov.materialize(cludata, vce)
     dof_absorb = 0
     for fe in fes
-        any(c->isnested(fe, c.refs), concrete_vcov.clusters) && (dof_absorb += 1)
+        any(c->isnested(fe, c.refs), concrete_vce.clusters) && (dof_absorb += 1)
     end
-    return concrete_vcov, dof_absorb
+    return concrete_vce, dof_absorb
 end
 
 """
@@ -362,19 +362,19 @@ end
 Estimate variance-covariance matrix and F-statistic.
 See also [`EstVcov`](@ref).
 """
-function estvcov(data, esample::BitVector, vcov::CovarianceEstimator, coef::Vector,
+function estvcov(data, esample::BitVector, vce::CovarianceEstimator, coef::Vector,
         X::Matrix, crossx::Factorization, residuals::Vector,
         xterms::Terms, fes::Vector{FixedEffect}, has_fe_intercept::Bool)
-    concrete_vcov, dof_absorb = _vcov(data, esample, vcov, fes)
+    concrete_vce, dof_absorb = _vce(data, esample, vce, fes)
     dof_resid = max(1, sum(esample) - size(X,2) - dof_absorb)
-    vcov_data = Vcov.VcovData(X, crossx, residuals, dof_resid)
-    vcov_mat = getvcov(vcov_data, concrete_vcov)
+    vce_data = Vcov.VcovData(X, crossx, residuals, dof_resid)
+    vcov_mat = vcov(vce_data, concrete_vce)
 
     # Fstat assumes the last coef is intercept if having any intercept
     has_intercept = !isempty(xterms) && isintercept(xterms[end])
     F = Fstat(coef, vcov_mat, has_intercept)
     has_intercept = has_intercept || has_fe_intercept
-    df_F = max(1, Vcov.df_FStat(vcov_data, concrete_vcov, has_intercept))
+    df_F = max(1, Vcov.df_FStat(vce_data, concrete_vce, has_intercept))
     p = fdistccdf(max(length(coef) - has_intercept, 1), df_F, F)
 
     return (vcov_mat=vcov_mat, dof_resid=dof_resid, F=F, p=p), true
@@ -390,5 +390,5 @@ may be shared across multiple specifications.
 """
 const EstVcov = StatsStep{:EstVcov, typeof(estvcov)}
 
-required(::EstVcov) = (:data, :esample, :vcov, :coef, :X, :crossx, :residuals, :xterms,
+required(::EstVcov) = (:data, :esample, :vce, :coef, :X, :crossx, :residuals, :xterms,
     :fes, :has_fe_intercept)

test/procedures.jl

@@ -1,8 +1,8 @@
 @testset "CheckVcov" begin
     hrs = exampledata("hrs")
-    nt = (data=hrs, esample=trues(size(hrs,1)), vcov=Vcov.robust())
+    nt = (data=hrs, esample=trues(size(hrs,1)), vce=Vcov.robust())
     @test checkvcov!(nt...) == (NamedTuple(), false)
-    nt = merge(nt, (vcov=Vcov.cluster(:hhidpn),))
+    nt = merge(nt, (vce=Vcov.cluster(:hhidpn),))
     @test checkvcov!(nt...) == ((esample=trues(size(hrs,1)),), false)
 
     @test CheckVcov()((data=hrs, esample=trues(size(hrs,1)))) ==
@@ -272,7 +272,7 @@ end
     crossx = cholesky!(Symmetric(X'X))
     coef = crossx \ (X'y)
     residuals = y - X * coef
-    nt = (data=hrs, esample=trues(nobs), vcov=Vcov.simple(), coef=coef,
+    nt = (data=hrs, esample=trues(nobs), vce=Vcov.simple(), coef=coef,
         X=X, crossx=crossx, residuals=residuals, xterms=(term(1),), fes=FixedEffect[],
         has_fe_intercept=false)
     ret, share = estvcov(nt...)
@@ -287,7 +287,7 @@ end
     @test ret.dof_resid == nobs - 3
     @test ret.F ≈ 10.68532285556941 atol=1e-6
 
-    nt = merge(nt, (vcov=Vcov.robust(), fes=FixedEffect[]))
+    nt = merge(nt, (vce=Vcov.robust(), fes=FixedEffect[]))
     ret, share = estvcov(nt...)
     # Compare estimates with Stata
     # reg oop_spend col0 col1, r
@@ -300,7 +300,7 @@ end
     @test ret.dof_resid == nobs - 3
     @test ret.F ≈ 5.371847047691197 atol=1e-6
 
-    nt = merge(nt, (vcov=Vcov.cluster(:hhidpn),))
+    nt = merge(nt, (vce=Vcov.cluster(:hhidpn),))
     ret, share = estvcov(nt...)
     # Compare estimates with Stata
     # reghdfe oop_spend col0 col1, noa clu(hhidpn)
@@ -321,7 +321,7 @@ end
     crossx = cholesky!(Symmetric(X'X))
     coef = crossx \ (X'y)
     residuals = y - X * coef
-    nt = merge(nt, (vcov=Vcov.robust(), coef=coef, X=X, crossx=crossx, residuals=residuals, xterms=(), fes=fes, has_fe_intercept=true))
+    nt = merge(nt, (vce=Vcov.robust(), coef=coef, X=X, crossx=crossx, residuals=residuals, xterms=(), fes=fes, has_fe_intercept=true))
     ret, share = estvcov(nt...)
     # Compare estimates with Stata
     # reghdfe oop_spend col0 col1, a(hhidpn) vce(robust)
@@ -332,7 +332,7 @@ end
     @test ret.dof_resid == nobs - nunique(fes[1]) - 2
     @test ret.F ≈ 7.559815337537517 atol=1e-6
 
-    nt = merge(nt, (vcov=Vcov.cluster(:hhidpn),))
+    nt = merge(nt, (vce=Vcov.cluster(:hhidpn),))
     ret, share = estvcov(nt...)
     # Compare estimates with Stata
     # reghdfe oop_spend col0 col1, a(hhidpn) clu(hhidpn)

test/runtests.jl

@@ -22,9 +22,9 @@ const tests = [
     "did"
 ]
 
-printstyled("Running tests:\n", color=:blue)
+printstyled("Running tests:\n", color=:blue, bold=true)
 
-for test in tests
+@time for test in tests
     include("$test.jl")
     println("\033[1m\033[32mPASSED\033[0m: $(test)")
 end