diff --git a/src/covariance.jl b/src/covariance.jl
index a4bb283..6bf5d0c 100644
--- a/src/covariance.jl
+++ b/src/covariance.jl
@@ -57,7 +57,7 @@ Base.range(cov::Covariance) = range(cov.γ)
 Scale metric ball of covariance `cov` with strictly
 positive scaling factor `s`.
 """
-scale(cov::Cov, s::Real) where {Cov <: Covariance} = Cov(scale(cov.γ, s))
+scale(cov::Cov, s::Real) where {Cov<:Covariance} = Cov(scale(cov.γ, s))
 
 """
     cov(g₁, g₂)
diff --git a/test/nesting.jl b/test/nesting.jl
index e2d0922..377500d 100644
--- a/test/nesting.jl
+++ b/test/nesting.jl
@@ -45,7 +45,7 @@
   γ = GaussianVariogram() + ExponentialVariogram()
   @test GeoStatsFunctions.returntype(γ, Point(0.0, 0.0, 0.0), Point(0.0, 0.0, 0.0)) == Float64
   γ = GaussianVariogram(sill=1.0f0, range=1.0f0, nugget=0.1f0)
-  @test GeoStatsFunctions.returntype(γ, Point(0f0, 0f0, 0f0), Point(0f0, 0f0, 0f0)) == Float32
+  @test GeoStatsFunctions.returntype(γ, Point(0.0f0, 0.0f0, 0.0f0), Point(0.0f0, 0.0f0, 0.0f0)) == Float32
 
   # nested model with matrix coefficients
   C₁ = [1.0 0.5; 0.5 2.0]