diff --git a/stat/combin/combin.go b/stat/combin/combin.go
index c15540f6..71145ac0 100644
--- a/stat/combin/combin.go
+++ b/stat/combin/combin.go
@@ -6,8 +6,6 @@ package combin
 
 import (
 	"math"
-
-	"gonum.org/v1/gonum/mat"
 )
 
 const (
@@ -185,49 +183,34 @@ func nextCombination(s []int, n, k int) {
 	}
 }
 
-// Cartesian returns the cartesian product of the slices in data. The Cartesian
+// Cartesian returns indices into the cartesian product for sets of the given lengths. The Cartesian
 // product of two sets is the set of all combinations of the items. For example,
 // given the input
-//  [][]float64{{1,2},{3,4},{5,6}}
+//  []int{2, 3, 1}
 // the returned matrix will be
-//  [ 1 3 5 ]
-//  [ 1 3 6 ]
-//  [ 1 4 5 ]
-//  [ 1 4 6 ]
-//  [ 2 3 5 ]
-//  [ 2 3 6 ]
-//  [ 2 4 5 ]
-//  [ 2 4 6 ]
-// If dst is nil, a new matrix will be allocated and returned, otherwise the number
-// of rows of dst must equal \prod_i len(data[i]), and the number of columns in
-// dst must equal len(data). Cartesian also panics if len(data) = 0.
-func Cartesian(dst *mat.Dense, data [][]float64) *mat.Dense {
-	if len(data) == 0 {
-		panic("combin: empty data input")
+//  [ 0 0 0 ]
+//  [ 0 1 0 ]
+//  [ 0 2 0 ]
+//  [ 1 0 0 ]
+//  [ 1 1 0 ]
+//  [ 1 2 0 ]
+// Cartesian panics if any of the provided lengths are less than 1.
+func Cartesian(lens []int) [][]int {
+	if len(lens) == 0 {
+		panic("combin: empty lengths")
 	}
-	cols := len(data)
 	rows := 1
-	lens := make([]int, cols)
-	for i, d := range data {
-		v := len(d)
-		lens[i] = v
+	for _, v := range lens {
+		if v < 1 {
+			panic("combin: length less than zero")
+		}
 		rows *= v
 	}
-	if dst == nil {
-		dst = mat.NewDense(rows, cols, nil)
-	}
-	r, c := dst.Dims()
-	if r != rows || c != cols {
-		panic("combin: destination matrix size mismatch")
-	}
-	idxs := make([]int, cols)
+	out := make([][]int, rows)
 	for i := 0; i < rows; i++ {
-		SubFor(idxs, i, lens)
-		for j := 0; j < len(data); j++ {
-			dst.Set(i, j, data[j][idxs[j]])
-		}
+		out[i] = SubFor(nil, i, lens)
 	}
-	return dst
+	return out
 }
 
 // IdxFor converts a multi-dimensional index into a linear index for a
diff --git a/stat/combin/combin_test.go b/stat/combin/combin_test.go
index ac41a3c1..ef884cb4 100644
--- a/stat/combin/combin_test.go
+++ b/stat/combin/combin_test.go
@@ -10,7 +10,6 @@ import (
 	"testing"
 
 	"gonum.org/v1/gonum/floats"
-	"gonum.org/v1/gonum/mat"
 )
 
 // intSosMatch returns true if the two slices of slices are equal.
@@ -184,62 +183,36 @@ func TestCombinationGenerator(t *testing.T) {
 
 func TestCartesian(t *testing.T) {
 	// First, test with a known return.
-	data := [][]float64{
-		{1, 2},
-		{3, 4},
-		{5, 6},
+	lens := []int{2, 3, 4}
+	want := [][]int{
+		{0, 0, 0},
+		{0, 0, 1},
+		{0, 0, 2},
+		{0, 0, 3},
+		{0, 1, 0},
+		{0, 1, 1},
+		{0, 1, 2},
+		{0, 1, 3},
+		{0, 2, 0},
+		{0, 2, 1},
+		{0, 2, 2},
+		{0, 2, 3},
+		{1, 0, 0},
+		{1, 0, 1},
+		{1, 0, 2},
+		{1, 0, 3},
+		{1, 1, 0},
+		{1, 1, 1},
+		{1, 1, 2},
+		{1, 1, 3},
+		{1, 2, 0},
+		{1, 2, 1},
+		{1, 2, 2},
+		{1, 2, 3},
 	}
-	want := mat.NewDense(8, 3, []float64{
-		1, 3, 5,
-		1, 3, 6,
-		1, 4, 5,
-		1, 4, 6,
-		2, 3, 5,
-		2, 3, 6,
-		2, 4, 5,
-		2, 4, 6,
-	})
-	got := Cartesian(nil, data)
-	if !mat.Equal(want, got) {
-		t.Errorf("cartesian data mismatch.\nwant:\n%v\ngot:\n%v", mat.Formatted(want), mat.Formatted(got))
-	}
-	gotTo := mat.NewDense(8, 3, nil)
-	Cartesian(gotTo, data)
-	if !mat.Equal(want, got) {
-		t.Errorf("cartesian data mismatch with supplied.\nwant:\n%v\ngot:\n%v", mat.Formatted(want), mat.Formatted(gotTo))
-	}
-
-	// Test that Cartesian generates unique vectors.
-	for cas, data := range [][][]float64{
-		{{1}, {2, 3}, {8, 9, 10}},
-		{{1, 10}, {2, 3}, {8, 9, 10}},
-		{{1, 10, 11}, {2, 3}, {8}},
-	} {
-		cart := Cartesian(nil, data)
-		r, c := cart.Dims()
-		if c != len(data) {
-			t.Errorf("Case %v: wrong number of columns. Want %v, got %v", cas, len(data), c)
-		}
-		wantRows := 1
-		for _, v := range data {
-			wantRows *= len(v)
-		}
-		if r != wantRows {
-			t.Errorf("Case %v: wrong number of rows. Want %v, got %v", cas, wantRows, r)
-		}
-		for i := 0; i < r; i++ {
-			for j := i + 1; j < r; j++ {
-				if floats.Equal(cart.RawRowView(i), cart.RawRowView(j)) {
-					t.Errorf("Cas %v: rows %d and %d are equal", cas, i, j)
-				}
-			}
-		}
-
-		cartTo := mat.NewDense(r, c, nil)
-		Cartesian(cartTo, data)
-		if !mat.Equal(cart, cartTo) {
-			t.Errorf("cartesian data mismatch with supplied.\nwant:\n%v\ngot:\n%v", mat.Formatted(cart), mat.Formatted(cartTo))
-		}
+	got := Cartesian(lens)
+	if !intSosMatch(want, got) {
+		t.Errorf("cartesian data mismatch.\nwant:\n%v\ngot:\n%v", want, got)
 	}
 }