update for new FixedEffectModels

Author: matthieugomez

src/InteractiveFixedEffectModels.jl

@@ -1,5 +1,4 @@
 module InteractiveFixedEffectModels
-
 ##############################################################################
 ##
 ## Dependencies

src/regife.jl

@@ -8,11 +8,6 @@ function regife(df::AbstractDataFrame, m::Model; kwargs...)
     regife(df, m.f; m.dict..., kwargs...)
 end
 
-#= salue 
-
-efe
-=#
-
 function regife(df::AbstractDataFrame, 
              f::Formula;
              ife::Union{Symbol, Expr, Nothing} = nothing, 
@@ -83,22 +78,24 @@ function regife(df::AbstractDataFrame,
     # Compute data needed for errors
     vcov_method_data = VcovMethod(df[esample, unique(Symbol.(vcov_vars))], vcovformula)
 
-    # Compute weights
-    sqrtw = get_weights(df, esample, weights)
-
+ 
     ## Compute factors, an array of AbtractFixedEffects
     if has_absorb
-        subdf = df[esample, unique(Symbol.(absorb_vars))]
-        fes = FixedEffect(subdf, feformula, sqrtw)
+        sqrtw = get_weights(df, trues(length(esample)), weights)
+        fixedeffects = FixedEffect(df, Terms(@eval(@formula(nothing ~ $(feformula)))), sqrtw)
+        fixedeffects = FixedEffect[x[esample] for x in fixedeffects]
         # in case some FixedEffect is a FixedEffectIntercept, remove the intercept
-        if any([typeof(f.interaction) <: Ones for f in fes]) 
+        if any([typeof(f.interactionname) <: Nothing for f in fixedeffects]) 
             rt.intercept = false
         end
-        pfe = FixedEffectProblem(fes, Val{:lsmr})
+        pfe = FixedEffectProblem(fixedeffects, Val{:lsmr})
     else
         pfe = nothing
     end
 
+    # Compute weights
+    sqrtw = get_weights(df, esample, weights)
+
     iterations = 0
     converged = false
     # get two dimensions
@@ -144,7 +141,9 @@ function regife(df::AbstractDataFrame,
     end
     y .= y .* sqrtw 
     oldy = copy(y)
-    residualize!(y, pfe, Int[], Bool[])
+    v1 = Int[]
+    v2 = Bool[]
+    residualize!(y, pfe, v1, v2)
 
     ##############################################################################
     ##
@@ -226,7 +225,7 @@ function regife(df::AbstractDataFrame,
         df_absorb_fe = 0
         if has_absorb 
             ## poor man adjustement of df for clustedered errors + fe: only if fe name != cluster name
-            for fe in fes
+            for fe in fixedeffects
                 if isa(vcovformula, VcovClusterFormula) && in(fe.factorname, vcov_vars)
                     df_absorb_fe += 0
                 else

src/types.jl

@@ -105,9 +105,21 @@ function getfactors(fp::AbstractFactorModel, fs::AbstractFactorSolution)
     # partial out Y and X with respect to i.id x factors and i.time x loadings
     newfes = FixedEffect[]
     for r in 1:rank(fp)
-        idfe = FixedEffect(fp.idrefs, size(fs.idpool, 1), fp.sqrtw, fs.timepool[fp.timerefs, r], :id, :time, :(idxtime))
+        idfe = FixedEffect(fp.idrefs, fp.sqrtw, zeros(size(fs.idpool, 1)), fs.timepool[fp.timerefs, r], :id, :time, :(idxtime))
+        for i in 1:length(idfe.refs)
+            idfe.scale[idfe.refs[i]] += abs2(idfe.interaction[i] * idfe.sqrtw[i])
+        end
+        for i in 1:length(idfe.scale)
+            idfe.scale[i] = idfe.scale[i] > 0 ? (1.0 / sqrt(idfe.scale[i])) : 0.
+        end
         push!(newfes, idfe)
-        timefe = FixedEffect(fp.timerefs, size(fs.timepool, 1), fp.sqrtw, fs.idpool[fp.idrefs, r], :time, :id, :(timexid))
+        timefe = FixedEffect(fp.timerefs, fp.sqrtw, zeros(size(fs.timepool, 1)), fs.idpool[fp.idrefs, r], :time, :id, :(timexid))
+        for i in 1:length(timefe.refs)
+            timefe.scale[timefe.refs[i]] += abs2(timefe.interaction[i] * timefe.sqrtw[i])
+        end
+        for i in 1:length(timefe.scale)
+            timefe.scale[i] = timefe.scale[i] > 0 ? (1.0 / sqrt(timefe.scale[i])) : 0.
+        end
         push!(newfes, timefe)
     end
     # obtain the residuals and cross