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slightly better performance (#257)
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* Update fit.jl

* Update fit.jl

* Update fixedeffects.jl

* Update fit.jl

* Update fixedeffects.jl

* Update fixedeffects.jl

* Update fixedeffects.jl

* Update fixedeffects.jl

* Update fixedeffects.jl

* simplify parsing

* update

* simplify a bit

* Update fit.jl

* Update fit.jl

* Update fit.jl

* Update fit.jl

* remove dof_ad

* Update fit.jl
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@matthieugomez
matthieugomez authored Dec 20, 2023
1 parent cf7c0f7 commit 8341322
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Showing 7 changed files with 195 additions and 223 deletions.
2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
name = "FixedEffectModels"
uuid = "9d5cd8c9-2029-5cab-9928-427838db53e3"
version = "1.10.2"
version = "1.11.0"

[deps]
DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
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8 changes: 4 additions & 4 deletions src/FixedEffectModel.jl
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Expand Up @@ -36,14 +36,14 @@ struct FixedEffectModel <: RegressionModel
# for FE
iterations::Int # Number of iterations
converged::Bool # Has the demeaning algorithm converged?
r2_within::Union{Float64, Nothing} # within r2 (with fixed effect
r2_within::Float64 # within r2 (with fixed effect

# for IV
F_kp::Union{Float64, Nothing} # First Stage F statistics KP
p_kp::Union{Float64, Nothing} # First Stage p value KP
F_kp::Float64 # First Stage F statistics KP
p_kp::Float64 # First Stage p value KP
end

has_iv(m::FixedEffectModel) = m.F_kp !== nothing
has_iv(m::FixedEffectModel) = has_iv(m.formula)
has_fe(m::FixedEffectModel) = has_fe(m.formula)


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305 changes: 129 additions & 176 deletions src/fit.jl
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5 changes: 3 additions & 2 deletions src/partial_out.jl
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Expand Up @@ -46,8 +46,9 @@ function partial_out(
f = FormulaTerm(f.lhs, tuple(ConstantTerm(1), eachterm(f.rhs)...))
end
formula, formula_endo, formula_iv = parse_iv(f)
has_iv = formula_iv !== nothing
has_iv = formula_iv != FormulaTerm(ConstantTerm(0), ConstantTerm(0))
has_iv && throw("partial_out does not support instrumental variables")
formula, formula_fes = parse_fe(formula)
has_weights = weights !== nothing


Expand All @@ -63,7 +64,7 @@ function partial_out(
convergeds = Bool[]

# Build fixedeffects, an array of AbtractFixedEffects
fes, ids, ids_fes, formula = parse_fixedeffect(df, formula)
fes, ids, ids_fes = parse_fixedeffect(df, formula_fes)
has_fes = !isempty(fes)


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12 changes: 12 additions & 0 deletions src/utils/fixedeffects.jl
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Expand Up @@ -4,6 +4,18 @@
##
##############################################################################

function drop_singletons!(esample, fes::Vector{<:FixedEffect})
ns = Int[]
for fe in Iterators.cycle(fes)
# break loop if number of singletons did not change since the last time fe was iterated on
if length(ns) >= length(fes) && sum(view(ns, (length(ns)-length(fes)+1):length(ns))) == ns[end-length(fes)+1]
break
end
push!(ns, drop_singletons!(esample, fe))
end
return sum(ns)
end

function drop_singletons!(esample, fe::FixedEffect)
n = 0
cache = zeros(Int, fe.n)
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64 changes: 35 additions & 29 deletions src/utils/formula.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -12,23 +12,24 @@ eachterm(@nospecialize(x::NTuple{N, AbstractTerm})) where {N} = x
## Parse IV
##
##############################################################################

has_iv(@nospecialize(f::FormulaTerm)) = any(x -> x isa FormulaTerm, eachterm(f.rhs))
function parse_iv(@nospecialize(f::FormulaTerm))
for term in eachterm(f.rhs)
if term isa FormulaTerm
both = intersect(eachterm(term.lhs), eachterm(term.rhs))
endos = setdiff(eachterm(term.lhs), both)
exos = setdiff(eachterm(term.rhs), both)
# otherwise empty collection. Later, there will be check
isempty(endos) && throw("There are no endogeneous variables")
length(exos) < length(endos) && throw("Model not identified. There must be at least as many instrumental variables as endogeneneous variables")
formula_endo = FormulaTerm(ConstantTerm(0), tuple(ConstantTerm(0), endos...))
formula_iv = FormulaTerm(ConstantTerm(0), tuple(ConstantTerm(0), exos...))
formula_exo = FormulaTerm(f.lhs, tuple((term for term in eachterm(f.rhs) if !isa(term, FormulaTerm))..., both...))
return formula_exo, formula_endo, formula_iv
end
end
return f, nothing, nothing
if has_iv(f)
i = findfirst(x -> x isa FormulaTerm, eachterm(f.rhs))
term = eachterm(f.rhs)[i]
both = intersect(eachterm(term.lhs), eachterm(term.rhs))
endos = setdiff(eachterm(term.lhs), both)
exos = setdiff(eachterm(term.rhs), both)
# otherwise empty collection. Later, there will be check
isempty(endos) && throw("There are no endogeneous variables")
length(exos) < length(endos) && throw("Model not identified. There must be at least as many instrumental variables as endogeneneous variables")
formula_endo = FormulaTerm(ConstantTerm(0), tuple(ConstantTerm(0), endos...))
formula_iv = FormulaTerm(ConstantTerm(0), tuple(ConstantTerm(0), exos...))
formula_exo = FormulaTerm(f.lhs, tuple((term for term in eachterm(f.rhs) if !isa(term, FormulaTerm))..., both...))
return formula_exo, formula_endo, formula_iv
else
return f, FormulaTerm(ConstantTerm(0), ConstantTerm(0)), FormulaTerm(ConstantTerm(0), ConstantTerm(0))
end
end

##############################################################################
Expand All @@ -47,13 +48,25 @@ has_fe(::FixedEffectTerm) = true
has_fe(::FunctionTerm{typeof(fe)}) = true
has_fe(@nospecialize(t::InteractionTerm)) = any(has_fe(x) for x in t.terms)
has_fe(::AbstractTerm) = false

has_fe(@nospecialize(t::FormulaTerm)) = any(has_fe(x) for x in eachterm(t.rhs))

function parse_fe(@nospecialize(f::FormulaTerm))
if has_fe(f)
formula_main = FormulaTerm(f.lhs, Tuple(term for term in eachterm(f.rhs) if !has_fe(term)))
formula_fe = FormulaTerm(ConstantTerm(0), Tuple(term for term in eachterm(f.rhs) if has_fe(term)))
return formula_main, formula_fe
else
return f, FormulaTerm(ConstantTerm(0), ConstantTerm(0))
end
end


fesymbol(t::FixedEffectTerm) = t.x
fesymbol(t::FunctionTerm{typeof(fe)}) = Symbol(t.args[1])




"""
parse_fixedeffect(data, formula::FormulaTerm)
parse_fixedeffect(data, ts::NTuple{N, AbstractTerm})
Expand All @@ -68,24 +81,17 @@ Construct any `FixedEffect` specified with a `FixedEffectTerm`.
"""
function parse_fixedeffect(data, @nospecialize(formula::FormulaTerm))
fes = FixedEffect[]
ids = Symbol[]
feids = Symbol[]
fekeys = Symbol[]
for term in eachterm(formula.rhs)
for term in eachterm(formula.rhs)
result = _parse_fixedeffect(data, term)
if result !== nothing
push!(fes, result[1])
push!(ids, result[2])
push!(feids, result[2])
append!(fekeys, result[3])
end
end
if !isempty(fes)
if any(fe.interaction isa UnitWeights for fe in fes)
formula = FormulaTerm(formula.lhs, (InterceptTerm{false}(), (term for term in eachterm(formula.rhs) if !isa(term, Union{ConstantTerm,InterceptTerm}) && !has_fe(term))...))
else
formula = FormulaTerm(formula.lhs, Tuple(term for term in eachterm(formula.rhs) if !has_fe(term)))
end
end
return fes, ids, unique(fekeys), formula
return fes, feids, unique(fekeys)
end

# Method for external packages
Expand All @@ -108,7 +114,7 @@ function parse_fixedeffect(data, @nospecialize(ts::NTuple{N, AbstractTerm})) whe
ts = Tuple(term for term in eachterm(ts) if !has_fe(term))
end
end
return fes, ids, unique(fekeys), ts
return fes, ids, unique(fekeys)
end

# Construct FixedEffect from a generic term
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22 changes: 11 additions & 11 deletions test/formula.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -22,13 +22,13 @@ for data in [df, csvfile]
@test _parse_fixedeffect(data, fe(:State)&fe(:Year)) ==
(FixedEffect(data.State, data.Year), Symbol("fe_State&fe_Year"), [:State, :Year])

@test parse_fixedeffect(data, ()) == (FixedEffect[], Symbol[], Symbol[], ())
@test parse_fixedeffect(data, ()) == (FixedEffect[], Symbol[], Symbol[])

f = @formula(y ~ 1 + Price)
ts1 = f.rhs
ts2 = term(1) + term(:Price)
@test parse_fixedeffect(data, f) == (FixedEffect[], Symbol[], Symbol[], f)
@test parse_fixedeffect(data, ts1) == (FixedEffect[], Symbol[], Symbol[], ts1)
@test parse_fixedeffect(data, f) == (FixedEffect[], Symbol[], Symbol[])
@test parse_fixedeffect(data, ts1) == (FixedEffect[], Symbol[], Symbol[])
@test parse_fixedeffect(data, ts2) == parse_fixedeffect(data, ts1)

fparsed = term(:y) ~ InterceptTerm{false}() + term(:Price)
Expand All @@ -37,28 +37,28 @@ for data in [df, csvfile]
f = @formula(y ~ 1 + Price + fe(State))
ts1 = f.rhs
ts2 = term(1) + term(:Price) + fe(:State)
@test parse_fixedeffect(data, f) == ([FixedEffect(data.State)], [:fe_State], [:State], fparsed)
@test parse_fixedeffect(data, ts1) == ([FixedEffect(data.State)], [:fe_State], [:State], tsparsed)
@test parse_fixedeffect(data, f) == ([FixedEffect(data.State)], [:fe_State], [:State])
@test parse_fixedeffect(data, ts1) == ([FixedEffect(data.State)], [:fe_State], [:State])
@test parse_fixedeffect(data, ts2) == parse_fixedeffect(data, ts1)

f = @formula(y ~ Price + fe(State) + fe(Year))
ts1 = f.rhs
ts2 = term(:Price) + fe(:State) + fe(:Year)
@test parse_fixedeffect(data, f) == ([FixedEffect(data.State), FixedEffect(data.Year)], [:fe_State, :fe_Year], [:State, :Year], fparsed)
@test parse_fixedeffect(data, ts1) == ([FixedEffect(data.State), FixedEffect(data.Year)], [:fe_State, :fe_Year], [:State, :Year], tsparsed)
@test parse_fixedeffect(data, f) == ([FixedEffect(data.State), FixedEffect(data.Year)], [:fe_State, :fe_Year], [:State, :Year])
@test parse_fixedeffect(data, ts1) == ([FixedEffect(data.State), FixedEffect(data.Year)], [:fe_State, :fe_Year], [:State, :Year])
@test parse_fixedeffect(data, ts2) == parse_fixedeffect(data, ts1)

f = @formula(y ~ Price + fe(State)&Year)
ts1 = f.rhs
ts2 = term(:Price) + fe(:State)&term(:Year)
@test parse_fixedeffect(data, f) == ([FixedEffect(data.State, interaction=_multiply(data, [:Year]))], [Symbol("fe_State&Year")], [:State], term(:y) ~ (term(:Price),))
@test parse_fixedeffect(data, ts1) == ([FixedEffect(data.State, interaction=_multiply(data, [:Year]))], [Symbol("fe_State&Year")], [:State], (term(:Price),))
@test parse_fixedeffect(data, f) == ([FixedEffect(data.State, interaction=_multiply(data, [:Year]))], [Symbol("fe_State&Year")], [:State])
@test parse_fixedeffect(data, ts1) == ([FixedEffect(data.State, interaction=_multiply(data, [:Year]))], [Symbol("fe_State&Year")], [:State])
@test parse_fixedeffect(data, ts2) == parse_fixedeffect(data, ts1)

f = @formula(y ~ Price + fe(State)*fe(Year))
ts1 = f.rhs
ts2 = term(:Price) + fe(:State) + fe(:Year) + fe(:State)&fe(:Year)
@test parse_fixedeffect(data, f) == ([FixedEffect(data.State), FixedEffect(data.Year), FixedEffect(data.State, data.Year)], [:fe_State, :fe_Year, Symbol("fe_State&fe_Year")], [:State, :Year], fparsed)
@test parse_fixedeffect(data, ts1) == ([FixedEffect(data.State), FixedEffect(data.Year), FixedEffect(data.State, data.Year)], [:fe_State, :fe_Year, Symbol("fe_State&fe_Year")], [:State, :Year], tsparsed)
@test parse_fixedeffect(data, f) == ([FixedEffect(data.State), FixedEffect(data.Year), FixedEffect(data.State, data.Year)], [:fe_State, :fe_Year, Symbol("fe_State&fe_Year")], [:State, :Year])
@test parse_fixedeffect(data, ts1) == ([FixedEffect(data.State), FixedEffect(data.Year), FixedEffect(data.State, data.Year)], [:fe_State, :fe_Year, Symbol("fe_State&fe_Year")], [:State, :Year])
@test parse_fixedeffect(data, ts2) == parse_fixedeffect(data, ts1)
end

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Registration pull request created: JuliaRegistries/General/97506

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Release notes:

## Breaking changes

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To add them here just re-invoke and the PR will be updated.

Tagging

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v1.11.0 -m "<description of version>" 83413220020d47efc88fe8909c43782578d566fb
git push origin v1.11.0

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