most of new dispatching for archimedean copulas

src/DatagenCopulaBased.jl

@@ -32,9 +32,11 @@ module DatagenCopulaBased
   # change Gaussian data by adding higher order cross-correlations
   include("add_higher_order_cors.jl")
 
-  export gaussian_cop, tstudent_cop, frechet, marshallolkin, gumbel, clayton, amh, frank
-  export rev_gumbel, rev_clayton, rev_amh
+  export clayton, amh, frank
+  export rev_clayton, rev_amh
 
+  export Gaussian_cop, Student_cop, Frechet_cop, Marshall_Olkin_cop
+  export Gumbel_cop, Gumbel_cop_rev, Clayton_cop, Clayton_cop_rev, AMH_cop, AMH_cop_rev
   export archcopulagen, chaincopulagen, nestedarchcopulagen
   export cormatgen, cormatgen_constant, cormatgen_toeplitz, convertmarg!, gcop2arch
   export cormatgen_constant_noised, cormatgen_toeplitz_noised, cormatgen_rand

src/add_higher_order_cors.jl

@@ -44,7 +44,7 @@ function gcop2tstudent(x::Matrix{Float64}, ind::Vector{Int}, ν::Int; naive::Boo
   μ = mean(x, dims = 1)
   y = (y.-μ)./S
   if naive
-    z = tstudent_cop(size(x,1), cor(x[:,ind]), ν)
+    z = simulate_copula1(size(x,1), Student_cop(cor(x[:,ind]), ν))
     y[:,ind] = quantile.(Normal(0,1), z)
   else
     U = rand(Chisq(ν), size(x, 1))
@@ -163,22 +163,6 @@ function gcop2frechet(x::Matrix{Float64}, inds::Vector{Int}; naive::Bool = false
   quantile.(Normal(0,1), x).*S.+μ
 end
 
-"""
-  frechet(α::Float64, u::Matrix{Float64})
-
-returns a matrix of size u with data generated using Frechet maximal copula with
-parameter α
-"""
-function frechet(α::Float64, u::Matrix{Float64})
-  for j in 1:size(u, 1)
-    if (rand() < α)
-      for i in 1:size(u,2)
-        u[j,i] = u[j, end]
-      end
-    end
-  end
-  u
-end
 
 """
   gcop2marshallolkin(x::Matrix{Float64}, inds::Vector{Int}, λ1::Float64 = 1., λ2::Float64 = 1.5; naive::Bool = false)