CompatHelper: bump compat for Optim to 2, (keep existing compat)

Project.toml

@@ -1,9 +1,10 @@
 name = "Copulas"
 uuid = "ae264745-0b69-425e-9d9d-cf662c5eec93"
-version = "0.1.33"
 authors = ["Oskar Laverny"]
+version = "0.1.33"
 
 [deps]
+ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
 Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
@@ -32,6 +33,7 @@ RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
 CopulasPlotsExt = ["Plots", "RecipesBase"]
 
 [compat]
+ADTypes = "1.21.0"
 Aqua = "v0.8"
 Combinatorics = "1"
 Distributions = "0.25"
@@ -43,7 +45,7 @@ LambertW = "1.0.0"
 LinearAlgebra = "1"
 LogExpFunctions = "0.3"
 MvNormalCDF = "0.2, 0.3"
-Optim = "1.13.2"
+Optim = "1.13.2, 2"
 Plots = "1"
 PolyLog = "2.6.0"
 Printf = "1"

src/ArchimedeanCopula.jl

@@ -239,7 +239,7 @@ function _fit(CT::Type{<:ArchimedeanCopula{d, GT} where {d, GT<:UnivariateGenera
         θ₀[1] = Distributions.params(_example(CT, d))[1]
     end
     f(θ) = -Distributions.loglikelihood(CT(d, θ[1]), U)
-    res = Optim.optimize(f, lo, hi,  θ₀, Optim.Fminbox(Optim.LBFGS()), autodiff = :forward)
+    res = Optim.optimize(f, lo, hi,  θ₀, Optim.Fminbox(Optim.LBFGS()), autodiff = ADTypes.AutoForwardDiff())
     θ     = Optim.minimizer(res)[1]
     return CT(d, θ), (; θ̂=(θ=θ,), optimizer=Optim.summary(res),
                         xtol=xtol, converged=Optim.converged(res), 

src/Copulas.jl

@@ -20,6 +20,7 @@ module Copulas
     import Optim
     import Printf
     import TaylorSeries
+    import ADTypes
 
     # Main code
     include("utils.jl")

src/ExtremeValueCopula.jl

@@ -161,7 +161,7 @@ function _fit(CT::Type{<:ExtremeValueCopula{d, GT} where {d, GT<:UnivariateTail2
     end
     θ0_clamped = clamp(θ0_val, lo, hi)
     f(θ) = -Distributions.loglikelihood(CT(d, θ[1]), U)
-    res = Optim.optimize(f, lo, hi, [θ0_clamped], Optim.Fminbox(Optim.LBFGS()), autodiff = :forward)
+    res = Optim.optimize(f, lo, hi, [θ0_clamped], Optim.Fminbox(Optim.LBFGS()), autodiff = ADTypes.AutoForwardDiff())
     θ̂ = Optim.minimizer(res)[1]
     return CT(d, θ̂), (; θ̂=(;θ=θ̂), optimizer=:GradientDescent,
                         xtol=xtol, converged=Optim.converged(res), 

src/Fitting.jl

@@ -86,7 +86,7 @@ function _fit(CT::Type{<:Copula}, U, ::Val{:mle})
     α₀  = _unbound_params(CT, d, Distributions.params(_example(CT, d)))
     loss(C) = -Distributions.loglikelihood(C, U)
     res = try
-        Optim.optimize(loss ∘ cop, α₀, Optim.LBFGS(); autodiff=:forward)
+        Optim.optimize(loss ∘ cop, α₀, Optim.LBFGS(); autodiff=ADTypes.AutoForwardDiff())
     catch err
         Optim.optimize(loss ∘ cop, α₀, Optim.NelderMead())
     end

src/MiscellaneousCopulas/FGMCopula.jl

@@ -161,7 +161,7 @@ function _fit(CT::Type{<:FGMCopula}, U, ::Val{:mle})
             α -> -Distributions.loglikelihood(FGMCopula(2, tanh(α[1])), U),
             [0.1], 
             Optim.LBFGS(); 
-            autodiff=:forward
+            autodiff=ADTypes.AutoForwardDiff()
         )
         θ = tanh(Optim.minimizer(res)[1])
         return CT(d, θ), (; θ̂=(θ=θ,), 
@@ -205,7 +205,7 @@ function _fit(CT::Type{<:FGMCopula}, U, ::Val{:mle})
     end
 
     # Optimise in θ-space directly (no need for unbound/rebound)
-    res = Optim.optimize(loss, θ₀, Optim.LBFGS(); autodiff=:forward)
+    res = Optim.optimize(loss, θ₀, Optim.LBFGS(); autodiff=ADTypes.AutoForwardDiff())
     θhat = Optim.minimizer(res)
     return FGMCopula(d, θhat),
         (; θ̂ = (θ = θhat,),