diff --git a/test/runtests.jl b/test/runtests.jl
index c6b8ed14..73419fbd 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -207,7 +207,7 @@ if test_set == "plots"
 
         back_grad = Zygote.gradient(x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
 
-        fin_grad = FiniteDifferences.grad(FiniteDifferences.central_fdm(3,1),x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
+        fin_grad = FiniteDifferences.grad(FiniteDifferences.central_fdm(4,1),x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
 
         @test isapprox(back_grad[1], fin_grad[1], rtol = 1e-6)
     end
@@ -229,7 +229,7 @@ if test_set == "plots"
 
         back_grad = Zygote.gradient(x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
 
-        fin_grad = FiniteDifferences.grad(FiniteDifferences.central_fdm(3,1, max_range = 1e-4),x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
+        fin_grad = FiniteDifferences.grad(FiniteDifferences.central_fdm(4,1, max_range = 1e-4),x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
 
         @test isapprox(back_grad[1], fin_grad[1], rtol = 1e-6)
     end
@@ -249,7 +249,7 @@ if test_set == "plots"
 
         back_grad = Zygote.gradient(x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
 
-        fin_grad = FiniteDifferences.grad(FiniteDifferences.central_fdm(3,1),x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
+        fin_grad = FiniteDifferences.grad(FiniteDifferences.central_fdm(4,1),x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
 
         @test isapprox(back_grad[1], fin_grad[1], rtol = 1e-6)
     end
@@ -269,7 +269,7 @@ if test_set == "plots"
 
         back_grad = Zygote.gradient(x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
 
-        fin_grad = FiniteDifferences.grad(FiniteDifferences.central_fdm(3,1),x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
+        fin_grad = FiniteDifferences.grad(FiniteDifferences.central_fdm(4,1),x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
 
         @test isapprox(back_grad[1], fin_grad[1], rtol = 1e-6)
     end
@@ -290,7 +290,7 @@ if test_set == "plots"
 
         back_grad = Zygote.gradient(x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
 
-        fin_grad = FiniteDifferences.grad(FiniteDifferences.central_fdm(3,1),x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
+        fin_grad = FiniteDifferences.grad(FiniteDifferences.central_fdm(4,1),x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
 
         @test isapprox(back_grad[1], fin_grad[1], rtol = 1e-6)
     end
@@ -312,7 +312,7 @@ if test_set == "plots"
 
         back_grad = Zygote.gradient(x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
 
-        fin_grad = FiniteDifferences.grad(FiniteDifferences.central_fdm(3,1),x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
+        fin_grad = FiniteDifferences.grad(FiniteDifferences.central_fdm(4,1),x-> get_loglikelihood(m, simulated_data(observables, :, :simulate), x), m.parameter_values)
 
         @test isapprox(back_grad[1], fin_grad[1], rtol = 1e-6)
     end