small adjustments + typo fixes

Author: tlienart

test/Project.toml

@@ -2,6 +2,7 @@
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
+Downloads = "f43a241f-c20a-4ad4-852c-f6b1247861c6"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MLJ = "add582a8-e3ab-11e8-2d5e-e98b27df1bc7"

test/benchmarks/robust.jl

@@ -2,9 +2,9 @@
 
 if DO_COMPARISONS
     @testset "Comp-QR-147" begin
-        using CSV, DataFrames
+        using CSV, DataFrames, Downloads
 
-        dataset = CSV.read(download("http://freakonometrics.free.fr/rent98_00.txt"), DataFrame)
+        dataset = CSV.read(Downloads.download("http://freakonometrics.free.fr/rent98_00.txt"), DataFrame)
         tau     = 0.3
 
         y  = Vector(dataset[!,:rent_euro])

test/fit/quantile.jl

@@ -74,7 +74,7 @@ end
 ## With Sparsity penalty ##
 ###########################
 
-Jn, p = 500, 100
+n, p = 500, 100
 ((X, y, θ), (X1, y1, θ1)) = generate_continuous(n, p;  seed=51112, sparse=0.1)
 # pepper with outliers
 y1a  = outlify(y1, 0.1)