replace Matrix type with AbstractMatrix

Author: jbytecode

src/basis.jl

@@ -290,7 +290,7 @@ end
 
 # Arguments
 - `f <: Function`: A function that takes a one dimensional array as argument.
-- `data::Matrix`: A Matrix object.
+- `data::AbstractMatrix`: A Matrix object.
 """
 function applyColumns(f::F, data::AbstractMatrix{Float64}) where {F <: Function}
     return [f(col) for col in eachcol(data)]

src/mve.jl

@@ -12,7 +12,7 @@ import ..Basis:
 import ..Diagnostics: mahalanobisSquaredMatrix
 
 
-function enlargesubset(initialsubset, data::DataFrame, dataMatrix::Matrix, h::Int)
+function enlargesubset(initialsubset, data::DataFrame, dataMatrix::AbstractMatrix, h::Int)
     n, _ = size(dataMatrix)
     basicsubset = copy(initialsubset)
     while length(basicsubset) < h

src/satman2015.jl

@@ -80,7 +80,7 @@ end
 Sort multidimensional data usin non-dominated sorting algorithm.
 
 # Arguments
-- `data::Matrix`: n x k matrix of observations where n is number of observations and k is number of variables.
+- `data::AbstractMatrix`: n x k matrix of observations where n is number of observations and k is number of variables.
 
 # Examples
 ```julia-repl
@@ -149,7 +149,7 @@ International Journal of Advanced Statistics and Probability 3.1 (2015): 53.
 Deb, Kalyanmoy, et al. "A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II." 
 International conference on parallel problem solving from nature. Springer, Berlin, Heidelberg, 2000.
 """
-function ndsranks(data::Matrix)::Array{Int}
+function ndsranks(data::AbstractMatrix)::Array{Int}
     n, _ = size(data)
     ranks = zeros(Int, n)
     mat = convert(Matrix, data)