CompatHelper: bump compat for TaylorSeries to 0.20, (keep existing compat) (#251)

Author: github-actions[bot]

Project.toml

@@ -41,7 +41,7 @@ SpecialFunctions = "2"
 StableRNGs = "1"
 StatsBase = "0.33, 0.34"
 StatsFuns = "0.9, 1.3"
-TaylorSeries = "0.15, 0.16, 0.17, 0.18"
+TaylorSeries = "0.15, 0.16, 0.17, 0.18, 0.19, 0.20"
 Test = "1"
 TestItemRunner = "1"
 WilliamsonTransforms = "0.1"

src/ArchimedeanCopula.jl

@@ -51,7 +51,7 @@ end
 ϕ(C::ArchimedeanCopula{d,TG},t)    where {d,TG} = ϕ(C.G,t)
 ϕ⁻¹(C::ArchimedeanCopula{d,TG},t)  where {d,TG} = ϕ⁻¹(C.G,t)
 ϕ⁽¹⁾(C::ArchimedeanCopula{d,TG},t) where {d,TG} = ϕ⁽¹⁾(C.G,t)
-ϕ⁽ᵏ⁾(C::ArchimedeanCopula{d,TG},k,t) where {d,TG} = ϕ⁽ᵏ⁾(C.G,k,t)
+ϕ⁽ᵏ⁾(C::ArchimedeanCopula{d,TG},t) where {d,TG} = ϕ⁽ᵏ⁾(C.G, Val(d), t)
 williamson_dist(C::ArchimedeanCopula{d,TG}) where {d,TG} = williamson_dist(C.G,d)
 
 
@@ -73,7 +73,7 @@ function Distributions._logpdf(C::ArchimedeanCopula{d,TG}, u) where {d,TG}
         sum_ϕ⁻¹u += ϕ⁻¹u
         logdenom += log(-ϕ⁽¹⁾(C,ϕ⁻¹u)) # log of negative here because ϕ⁽¹⁾ is necessarily negative
     end
-    numer = abs(ϕ⁽ᵏ⁾(C, d, sum_ϕ⁻¹u))
+    numer = abs(ϕ⁽ᵏ⁾(C, sum_ϕ⁻¹u))
     if numer > 0
         r = log(numer) - logdenom
         !isnan(r) && return r

src/Generator.jl

@@ -35,10 +35,8 @@ max_monotony(G::Generator) = throw("This generator does not have a defined max m
 ϕ(   G::Generator, t) = throw("This generator has not been defined correctly, the function `ϕ(G,t)` is not defined.")
 ϕ⁻¹( G::Generator, x) = Roots.find_zero(t -> ϕ(G,t) - x, (0.0, Inf))
 ϕ⁽¹⁾(G::Generator, t) = ForwardDiff.derivative(x -> ϕ(G,x), t)
-function ϕ⁽ᵏ⁾(G::Generator, k, t)
-    X = TaylorSeries.Taylor1(eltype(t),k)
-    taylor_expansion = ϕ(G,t+X)
-    coef = TaylorSeries.getcoeff(taylor_expansion,k) 
+function ϕ⁽ᵏ⁾(G::Generator, ::Val{k}, t) where k
+    coef = WilliamsonTransforms.taylor(x -> ϕ(G, x), t, k)[end]
     der = coef * factorial(k)
     return der
 end

src/Generator/UnivariateGenerator/JoeGenerator.jl

@@ -36,17 +36,14 @@ struct JoeGenerator{T} <: UnivariateGenerator
         end
     end
 end
-max_monotony(G::JoeGenerator) = Inf
+max_monotony(::JoeGenerator) = Inf
 ϕ(  G::JoeGenerator, t) = 1-(-expm1(-t))^(1/G.θ)
 ϕ⁻¹(G::JoeGenerator, t) = -log1p(-(1-t)^G.θ)
 # ϕ⁽¹⁾(G::JoeGenerator, t) =  First derivative of ϕ
-function ϕ⁽ᵏ⁾(G::JoeGenerator, k, t)
-    t==0 && return iseven(k) ? Inf : -Inf
-    X = TaylorSeries.Taylor1(eltype(t),k)
-    taylor_expansion = ϕ(G,t+X)
-    coef = TaylorSeries.getcoeff(taylor_expansion,k) 
-    der = coef * factorial(k)
-    return der
+function ϕ⁽ᵏ⁾(G::JoeGenerator, ::Val{k}, t) where k
+    t==0 && return iseven(k) ? eltype(t)(Inf) : eltype(t)(-Inf)
+    t==Inf && return zero(t)
+    return @invoke ϕ⁽ᵏ⁾(G::Generator, Val(k), t) 
 end
 τ(G::JoeGenerator) = 1 - 4sum(1/(k*(2+k*G.θ)*(G.θ*(k-1)+2)) for k in 1:1000) # 446 in R copula. 
 function τ⁻¹(::Type{T},tau) where T<:JoeGenerator 

test/WilliamsonCopula.jl

@@ -2,17 +2,17 @@
 @testitem "williamson test" begin
     using Distributions, Random
     using StableRNGs
-    rng = StableRNG(123)
+    rng = StableRNG(12)
     taus = [0.0, 0.1, 0.5, 0.9, 1.0]
 
-    ϕ_clayton(x, θ) = max((1 + θ * x),zero(x))^(-1/θ)
+    # ϕ_clayton(x, θ) = max((1 + θ * x),zero(x))^(-1/θ)
 
     Cops = (
         ArchimedeanCopula(10,i𝒲(Dirac(1),10)),
         ArchimedeanCopula(2,i𝒲(Pareto(1),5)),
         ArchimedeanCopula(2,i𝒲(LogNormal(3),5)),
     )
     for C in Cops
-        x = rand(rng,C,10)
+        rand(rng,C,10)
     end
 end