Vect->AbstractVec in fit_routine and pvalue

src/juobs_tools.jl

@@ -1312,7 +1312,7 @@ function fit_routine(model::Function,
     [uwerr(y, wpm) for y in ydata]
     if length(W) ==0
         if corr 
-            C = length(C) ==0 ? ADerrors.cov(ydata,wpm) : C
+            C = length(C) ==0 ? GammaMethod.cov_AD(ydata,wpm) : C
             W = LinearAlgebra.pinv(C);
             W = (W'+W)*0.5
         else
@@ -1566,9 +1566,9 @@ Q = pvalue(chisq, chi2, value.(up), y, wpm; W = 1.0 ./ err.(y) .^ 2, nmc=10000)
 """
 function pvalue(chisq::Function,
     chi2::Float64,
-    xp::Vector{Float64}, 
-    data::Vector{uwreal},
-    W::Vector{Float64}=Vector{Float64}();
+    xp::AbstractVector{Float64}, 
+    data::AbstractVector{uwreal},
+    W::AbstractVector{Float64}=Vector{Float64}();
     wpm::Union{Dict{Int64,Vector{Float64}},Dict{String,Vector{Float64}}, Nothing} =  Dict{Int64,Vector{Float64}}(),
     nmc::Int64 = 5000,
     C::AbstractMatrix{Float64} = ADerrors.cov(data,wpm))
@@ -1644,9 +1644,9 @@ end
 
 function pvalue(chisq::Function,
     chi2::Float64,
-    xp::Vector{Float64}, 
-    data::Vector{uwreal},
-    W::Array{Float64,2};
+    xp::AbstractVector{Float64}, 
+    data::AbstractVector{uwreal},
+    W::AbstractArray{Float64,2};
     wpm::Union{Dict{Int64,Vector{Float64}},Dict{String,Vector{Float64}}, Nothing} =  Dict{Int64,Vector{Float64}}(),
     nmc::Int64 = 5000,
     C::AbstractMatrix{Float64} = ADerrors.cov(data,wpm))