Move MvNormalCDF to test-only dependencies

Author: lrnv

Project.toml

@@ -4,14 +4,14 @@ version = "0.1.33"
 authors = ["Oskar Laverny"]
 
 [deps]
+BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
 Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 HCubature = "19dc6840-f33b-545b-b366-655c7e3ffd49"
 LambertW = "984bce1d-4616-540c-a9ee-88d1112d94c9"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LogExpFunctions = "2ab3a3ac-af41-5b50-aa03-7779005ae688"
-MvNormalCDF = "37188c8d-bc69-4638-b057-733e744175ec"
 Optim = "429524aa-4258-5aef-a3af-852621145aeb"
 PolyLog = "85e3b03c-9856-11eb-0374-4dc1f8670e7f"
 Primes = "27ebfcd6-29c5-5fa9-bf4b-fb8fc14df3ae"
@@ -20,6 +20,7 @@ QuadGK = "1fd47b50-473d-5c70-9696-f719f8f3bcdc"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Roots = "f2b01f46-fcfa-551c-844a-d8ac1e96c665"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
+StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 StatsFuns = "4c63d2b9-4356-54db-8cca-17b64c39e42c"
@@ -34,6 +35,7 @@ CopulasPlotsExt = ["Plots", "RecipesBase"]
 
 [compat]
 Aqua = "v0.8"
+BenchmarkTools = "1.6.0"
 Combinatorics = "1"
 Distributions = "0.25"
 ForwardDiff = "0.10, 1"
@@ -67,6 +69,7 @@ Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 HypothesisTests = "09f84164-cd44-5f33-b23f-e6b0d136a0d5"
 InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+MvNormalCDF = "37188c8d-bc69-4638-b057-733e744175ec"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

src/Copulas.jl

@@ -10,7 +10,6 @@ module Copulas
     import StatsFuns
     import ForwardDiff
     import HCubature
-    import MvNormalCDF
     import Combinatorics
     import LogExpFunctions
     import QuadGK

src/EllipticalCopulas/GaussianCopula.jl

@@ -143,15 +143,10 @@ function qmc_orthant_normal!(Σ::AbstractMatrix{T}, b::AbstractVector{T}; m::Int
     (ch, bs) = _chlrdr_orthant!(Σ, b)    # ¡muta Σ y b!
     qmc_orthant_core!(ch, bs; m=m, r=r, rng=rng)
 end
-function Distributions.cdf(C::CT, u::AbstractVector; method::Symbol = :qmc, m::Integer = 1000*length(C), r::Int = 12, rng = Random.default_rng()) where {CT<:GaussianCopula}
+function Distributions.cdf(C::GaussianCopula{d, MT}, u::AbstractVector; m::Integer = 1000*d, r::Int = 12, rng = Random.default_rng()) where {d, MT}
     x = StatsBase.quantile.(Distributions.Normal(), u)
-    d = length(C)
-    if method == :qmc
-        Tx = eltype(x)
-        Σ_promoted = Tx.(copy(C.Σ))
-        p, _ = qmc_orthant_normal!(Σ_promoted, x; m=m, r=r, rng=rng)
-    elseif method == :normal
-        p = MvNormalCDF.mvnormcdf(C.Σ, fill(-Inf, d), x)[1]
-    end
+    Tx = eltype(x)
+    Σ_promoted = Tx.(copy(C.Σ))
+    p, _ = qmc_orthant_normal!(Σ_promoted, x; m=m, r=r, rng=rng)
     return p
 end