Fix some issues

junyuan-chen · Apr 20, 2024 · 9485386 · 9485386
1 parent afc9a32
commit 9485386
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Showing 2 changed files with 75 additions and 24 deletions.
diff --git a/src/dfm.jl b/src/dfm.jl
@@ -106,25 +106,31 @@ end
 
 nfactor(f::DynamicFactor) = nfactor(f.f)
 
-function _dfm_est!(Y, facX, crossfacX, Λ, u, lagca, crosslagca, arcoef, resid, σ, narlag)
+function _dfm_est!(Y, facX, crossfacX, Λ, u, lagca, crosslagca, arcoef, resid, σ, narlag, arexclude)
     Tfull, N = size(Y)
     # Estimate coefficients for common components
     Y1 = view(Y, Tfull-size(facX,1)+1:Tfull, :)
     _ols!(Y1, facX, crossfacX, Λ, u)
     T = size(lagca, 1)
     T1 = size(u, 1)
     t1 = T1 - T + 1
-    dofr = size(lagca, 1) - size(lagca, 2)
+    dofr = T - narlag
     # Estimate coefficients for idiosyncratic components
     for n in 1:N
         coefn = view(arcoef, :, n)
         un = view(u, t1:T1, n)
         residn = view(resid, :, n)
-        for l in 1:narlag
-            lagca[:,l] .= view(u, t1-l:T1-l, n)
+        if arexclude !== nothing && n in arexclude
+            fill!(coefn, zero(eltype(coefn)))
+            copyto!(residn, un)
+            σ[n] = sqrt(sum(abs2, residn) / T)
+        else
+            for l in 1:narlag
+                lagca[:,l] .= view(u, t1-l:T1-l, n)
+            end
+            _ols!(un, lagca, crosslagca, coefn, residn)
+            σ[n] = sqrt(sum(abs2, residn) / dofr)
         end
-        _ols!(un, lagca, crosslagca, coefn, residn)
-        σ[n] = sqrt(sum(abs2, residn) / dofr)
     end
 end
 
@@ -133,7 +139,7 @@ function DynamicFactor(Y::AbstractMatrix, facobs::Union{AbstractVecOrMat, Nothin
         FacProc::Union{Type, Nothing}, nfaclag::Integer, narlag::Integer,
         X::Union{AbstractVecOrMat, Nothing}=nothing;
         svdalg::Algorithm=default_svd_alg(Y), maxiter::Integer=10000, tol::Real=1e-8,
-        facprockwargs::NamedTuple=NamedTuple())
+        arexclude=nothing, facprockwargs::NamedTuple=NamedTuple())
     Y = convert(Matrix, Y)
     Tfull, N = size(Y)
     nsk = nskip(trans)
@@ -149,7 +155,7 @@ function DynamicFactor(Y::AbstractMatrix, facobs::Union{AbstractVecOrMat, Nothin
         size(facobs, 1) == Tfull || throw(DimensionMismatch(
             "facobs and Y do not have the same number of rows"))
         facobs = convert(Matrix, facobs)
-        facobs0 = similar(facobs, T-nsk, size(facobs,2))
+        facobs0 = similar(facobs, Tfull-nsk, size(facobs,2))
         detrend!(trans, facobs0, facobs)
     end
     f = Factor(Y0, facobs0, nfac; svdalg=svdalg, maxiter=maxiter, tol=tol)
@@ -175,7 +181,8 @@ function DynamicFactor(Y::AbstractMatrix, facobs::Union{AbstractVecOrMat, Nothin
     arcoef = similar(Y, narlag, N)
     resid = similar(Y, T, N)
     σ = similar(Y, N)
-    _dfm_est!(Y, facX, crossfacX, Λ, u, lagca, crosslagca, arcoef, resid, σ, narlag)
+    _dfm_est!(Y, facX, crossfacX, Λ, u, lagca, crosslagca, arcoef, resid, σ,
+        narlag, arexclude)
     if FacProc !== nothing
         facproc = fit(FacProc, view(facX,:,1:nfac), nfaclag; facprockwargs...)
     else
@@ -186,17 +193,17 @@ function DynamicFactor(Y::AbstractMatrix, facobs::Union{AbstractVecOrMat, Nothin
 end
 
 function fit!(f::DynamicFactor; maxiter::Integer=10000, tol::Real=1e-8,
-        facprockwargs::NamedTuple=NamedTuple())
+        arexclude=nothing, facprockwargs::NamedTuple=NamedTuple())
     detrend!(f.trans, f.Y0, f.Y)
     if f.facobs !== nothing
-        facobs0 = nothing
-        detrend!(f.trans, facobs0, facobs)
+        detrend!(f.trans, f.facobs0, f.facobs)
+        copyto!(view(f.f.fac,:,1:f.f.nfaco), f.facobs0)
     end
     fit!(f.f; maxiter=maxiter, tol=tol)
     nfac = size(f.f.fac, 2)
     invdetrend!(f.trans, view(f.facX,:,1:nfac), f.f.fac)
     _dfm_est!(f.Y, f.facX, f.crossfacX, f.Λ, f.u, f.lagca, f.crosslagca, f.arcoef, f.resid,
-        f.σ, f.narlag)
+        f.σ, f.narlag, arexclude)
     f.facproc === nothing ||
         fit!(f.facproc, view(f.facX,:,1:nfac); facprockwargs...)
     return f
@@ -216,12 +223,17 @@ When only unobserved factors are involved,
 the number of factors may be selected based on a defined criterion.
 The type of the model for the evolution of factors
 may be specified with `FacProc`.
+See also [`DynamicFactor`](@ref) and [`fit!`](@ref).
+
 The meaning of the remaining arguments matches
 the corresponding fields in [`DynamicFactor`](@ref).
 All keyword arguments for fitting [`Factor`](@ref) are accepted.
-Any keyword argument for `FacProc` may be provided
-as a `NamedTuple` for the keyword `facprockwargs`.
-See also [`DynamicFactor`](@ref) and [`fit!`](@ref).
+The following are the additional keywords accepted.
+
+# Keywords
+- `arexclude=nothing`: set of indices for variables to be excluded from estimating
+the autoregressive coefficients of the idiosyncratic components.
+- `facprockwargs::NamedTuple=NamedTuple()`: keyword argument for `FacProc`.
 
 # Reference
 **Stock, James H. and Mark W. Watson.** 2016.
@@ -235,11 +247,12 @@ function fit(::Type{<:DynamicFactor}, data, names, fonames, trans::AbstractDetre
         X::Union{AbstractVecOrMat, Nothing}=nothing;
         subset::Union{BitVector, Nothing}=nothing, TF::Type=Float64,
         svdalg::Algorithm=DivideAndConquer(), maxiter::Integer=10000, tol::Real=1e-8,
-        facprockwargs::NamedTuple=NamedTuple())
+        arexclude=nothing, facprockwargs::NamedTuple=NamedTuple())
     Y, faco = _factor_tabletomat(data, names, fonames, subset, TF)
     X !== nothing && subset !== nothing && (X = view(X, subset, :))
     return DynamicFactor(Y, faco, trans, nfac, FacProc, nfaclag, narlag, X;
-        svdalg=svdalg, maxiter=maxiter, tol=tol, facprockwargs=facprockwargs)
+        svdalg=svdalg, maxiter=maxiter, tol=tol,
+        arexclude=arexclude, facprockwargs=facprockwargs)
 end
 
 show(io::IO, f::DynamicFactor) =

diff --git a/test/dfm.jl b/test/dfm.jl
@@ -98,16 +98,54 @@ end
           Not estimated"""
     end
 
-    f2 = fit(DynamicFactor, tb, ibal, nothing, FirstDiff(), BaiNg(30),
+    w = data[2:end,1:1]
+    f2 = DynamicFactor(xbal, w, FirstDiff(), 4, nothing, 4, 4, 1:223, arexclude=(1,))
+    @test abs.(f2.facX[10,1:4]) ≈ abs.([2.647070534273070, -0.409233763390545,
+        -2.448583354331101, 0.777062133958662]) atol=1e-10
+    @test abs.(f2.Λ[1:4,:]') ≈ abs.([
+        1.000000000000000  -0.000000000000085  -0.000000000000253  -0.000000000000277;
+       -0.176869660254340   0.341326133790815  -0.531832560474252  -0.050548484398590;
+        0.138280288564886   0.176289518804467  -0.003579973854560   0.127784818344253;
+       -0.017376912623149   1.389248038370042   1.590214827285696   0.053961254580756;
+       -0.288853468488554   1.295956580093574   1.340073720674857   0.376761035586924;
+        0.741342427554159   0.746936517706743  -0.836747380775329  -0.637279129786421;
+       -0.000057553428649   0.000331665615867   0.000731261496305   0.000272838958179;
+       -0.146403622040140  -0.016342164982163   0.008833758737728   1.871736796403937
+    ]) atol=1e-10
+    @test f2.arcoef' ≈
+        [               0                   0                   0                   0;
+        0.616037967310018   0.107591400424874   0.069023223680326   0.043873141740624;
+        0.769836475718294  -0.022464276053618   0.061128324277641   0.072377642177374;
+        0.573263857098401   0.120224782292888   0.044175367824055  -0.054197784792354;
+        0.746501793004697   0.124187288728450   0.044444174053458  -0.125784699949580;
+        1.030744790868324   0.093747757564231  -0.116526277928615  -0.082567084371622;
+        0.511383934328558   0.102277378712291   0.059272962038230  -0.059105468722871;
+        0.560208207607704   0.105367527318873   0.098177242590535  -0.027960067387970
+        ] atol=1e-10
+    @test f2.σ[2:end] ≈ [0.412619331990811, 0.617549404907423, 1.252061775182155,
+        1.315822943598192, 3.738078775682554, 0.002967937991064, 0.615717221130628
+        ] atol=1e-10
+
+    f21 = deepcopy(f2)
+    fill!(f21.Y0, 0)
+    fill!(f21.facobs0, 0)
+    fill!(f21.f.fac, 0)
+    fill!(f21.arcoef, 0)
+    fit!(f21, arexclude=1)
+    @test f21.f.fac ≈ f2.f.fac
+    @test f21.Λ ≈ f2.Λ
+    @test f21.arcoef ≈ f2.arcoef
+
+    f3 = fit(DynamicFactor, tb, ibal, nothing, FirstDiff(), BaiNg(30),
         VAROLS, 4, 4, 1:224; subset=(1:224).>1)
-    @test abs.(f2.facX[1,1:3]) ≈
+    @test abs.(f3.facX[1,1:3]) ≈
         abs.([2.633579135057327, -4.515438104711660, 0.967695227734307]) atol=1e-10
-    @test abs.(f2.facX[20,1:3]) ≈
+    @test abs.(f3.facX[20,1:3]) ≈
         abs.([-11.213179331809721, -10.755437451370934, -9.740548002249279]) atol=1e-10
     # Li, Plagborg-Møller and Wolf (2024) has an initial row of zeros
     # for lagmatrix generated from cumsum_nan
     # Removing the initial row yields the same estimates here
-    @test abs.(coef(f2.facproc)) ≈
+    @test abs.(coef(f3.facproc)) ≈
         abs.([0.673856090754789  -0.081037456424403  -0.490680042824428;
          1.616377319397290   0.296011178122282  -0.131965176312504;
         -0.244663060538245   1.369015986230120  -0.098455471141018;
@@ -121,10 +159,10 @@ end
         -0.215963192051662  -0.118458036521081  -0.102091302758074;
          0.026271389380724  -0.163505737633263  -0.041529088862164;
         -0.179952139267754   0.145787466313025  -0.151287681694109]) atol=1e-10
-    @test sprint(show, f2) ==
+    @test sprint(show, f3) ==
         "222×3 DynamicFactor{Float64, FirstDiff, Nothing, Factor{Float64, SDDcache{Float64}}, VAROLS{Float64, Vector{Float64}, Nothing, Nothing, Nothing}}"
     if VERSION >= v"1.7"
-    @test sprint(show, MIME("text/plain"), f2, context=:displaysize=>(10,120)) == """
+    @test sprint(show, MIME("text/plain"), f3, context=:displaysize=>(10,120)) == """
         222×3 DynamicFactor{Float64, FirstDiff, Nothing, Factor{Float64, SDDcache{Float64}}, VAROLS{Float64, Vector{Float64}, Nothing, Nothing, Nothing}} with 3 unobserved factors and 0 observed factor:
           2.63358  4.51544  -0.967695
           ⋮