``````# Tests for Cost DEA Models
@testset "CostDEAModel" begin

## Test Cost DEA Model with Cooper et al. (2007)
# Test agains book results
X = [3 2; 1 3; 4 6]
Y = [3; 5; 6]
W = [4 2; 4 2; 4 2]

deacostcooper = deacost(X, Y, W, rts = :CRS)

@test typeof(deacostcooper) == CostDEAModel

@test nobs(deacostcooper) == 3
@test ninputs(deacostcooper) == 2
@test noutputs(deacostcooper) == 1
@test ismonetary(deacostcooper) == false

@test efficiency(deacostcooper, :Economic)   ≈ [0.375; 1; 0.429] atol = 1e-3
@test efficiency(deacostcooper, :Technical)  ≈ [0.9  ; 1; 0.6  ] atol = 1e-3
@test efficiency(deacostcooper, :Allocative) ≈ [0.417; 1; 0.714] atol = 1e-3

## Test Cost DEA Model with Zofío and Prieto (2006) data.
# Test agains results in R
X = [5 3; 2 4; 4 2; 4 8; 7 9]
Y = [7 4; 10 8; 8 10; 5 4; 3 6]
W = [2 1; 2 1; 2 1; 2 1; 2 1.0]

# Cost CRS
deacostcrs = deacost(X, Y, W, rts = :CRS)
@test efficiency(deacostcrs) ≈ [0.4307692308;
1.000;
1.000;
0.250;
0.2608695652]
@test efficiency(deacostcrs, :Technical) ≈ [0.6364;
1.000;
1.000;
0.250;
0.2609]  atol = 1e-3
@test efficiency(deacostcrs, :Allocative) ≈ [0.6769230769;
1.000;
1.000;
1.000;
1.000]

@test efficiency(deacost(targets(deacostcrs, :X), targets(deacostcrs, :Y), W, rts = :CRS)) ≈ ones(5)

# Cost VRS
deacostvrs = deacost(X, Y, W, rts = :VRS)
@test efficiency(deacostvrs) ≈ [0.6153846154;
1.000;
1.000;
0.500;
0.3478260870]
@test efficiency(deacostvrs, :Technical) ≈ [0.750;
1.000;
1.000;
0.500 ;
0.375]  atol = 1e-3
@test efficiency(deacostvrs, :Allocative) ≈ [0.8205128205;
1.000;
1.000;
1.000;
0.9275362319]

@test efficiency(deacost(targets(deacostvrs, :X), targets(deacostvrs, :Y), W, rts = :VRS)) ≈ ones(5)

# Check defaults
@test efficiency(deacost(X, Y, W)) == efficiency(deacostvrs)
@test efficiency(deacostvrs, :Economic) == efficiency(deacostvrs)

# Print
show(IOBuffer(), deacostcooper)

# Test errors
@test_throws DimensionMismatch deacost([1; 2 ; 3], [4 ; 5], [1; 1; 1]) #  Different number of observations
@test_throws DimensionMismatch deacost([1; 2; 3], [4; 5; 6], [1; 2; 3; 4]) # Different number of observation in prices
@test_throws DimensionMismatch deacost([1 1; 2 2; 3 3 ], [4; 5; 6], [1 1 1; 2 2 2; 3 3 3]) # Different number of input prices and inputs
@test_throws ArgumentError deacost([1; 2; 3], [4; 5; 6], [1; 2; 3], rts = :Error) # Invalid returns to scale
@test_throws ArgumentError deacost([1; 2; 3], [4; 5; 6], [1; 2; 3], dispos = :Error) # Invalid disposability
@test_throws ArgumentError normfactor(deacost(X, Y, W)) # CostDEAModel has no normalization factor

# ------------------
# Weak Disposability Tests
# ------------------

X = [1; 2; 3; 2; 4]
Y = [2; 3; 4; 1; 3]
W = [1; 1; 1; 1; 1]

deacostStrong = deacost(X, Y, W, dispos = :Strong)
@test efficiency(deacostStrong, :Economic) ≈ [1.0; 1.0; 1.0; 0.5; 0.5]
@test efficiency(deacostStrong, :Technical) ≈ [1.0; 1.0; 1.0; 0.5; 0.5]
@test efficiency(deacostStrong, :Allocative) ≈ [1.0; 1.0; 1.0; 1.0; 1.0]

deacostWeak = deacost(X, Y, W, dispos = :Weak)
@test efficiency(deacostWeak, :Economic) ≈ [1.0; 1.0; 1.0; 1.0; 0.5]
@test efficiency(deacostWeak, :Technical) ≈ [1.0; 1.0; 1.0; 1.0; 0.5]
@test efficiency(deacostWeak, :Allocative) ≈ [1.0; 1.0; 1.0; 1.0; 1.0]

# ------------------
# Test Vector and Matrix inputs and outputs
# ------------------
# Tests against results in R

# Inputs is Matrix, Outputs is Vector
X = [2 2; 1 4; 4 1; 4 3; 5 5; 6 1; 2 5; 1.6	8]
Y = [1; 1; 1; 1; 1; 1; 1; 1]
W = [1 1; 1 1; 1 1; 1 1; 1 1; 1 1; 1 1; 1 1]

@test efficiency(deacost(X, Y, W)) ≈ [1; 0.8; 0.8; 0.5714285714; 0.4; 0.5714285714; 0.5714285714; 0.4166666667]

# Inputs is Vector, Output is Matrix
X = [1; 1; 1; 1; 1; 1; 1; 1]
Y = [7 7; 4 8; 8 4; 3 5; 3 3; 8 2; 6 4; 1.5 5]
W = [1; 1; 1; 1; 1; 1; 1; 1]

@test efficiency(deacost(X, Y, W)) ≈ [1; 1; 1; 1; 1; 1; 1; 1]

# Inputs is Vector, Output is Vector
X = [2; 4; 8; 12; 6; 14; 14; 9.412]
Y = [1; 5; 8; 9; 3; 7; 9; 2.353]
W = [1; 1; 1; 1; 1; 1; 1; 1]

@test efficiency(deacost(X, Y, W)) ≈ [1; 1; 1; 1; 0.5; 0.4761904762; 0.8571428571; 0.2843710157]

end
``````