diff --git a/docs/content/Interpolation.md b/docs/content/Interpolation.md
index 384e1d71..5f298153 100644
--- a/docs/content/Interpolation.md
+++ b/docs/content/Interpolation.md
@@ -37,12 +37,13 @@ Interpolation on arbitrary sample points
 ----------------------------------------
 
 * *Rational pole-free*: Barycentric Floater-Hormann Algorithm
-* **Rational with poles**: Bulirsch & Stoer Algorithm
+* *Rational with poles*: Bulirsch & Stoer Algorithm
 * *Neville Polynomial*: Neville Algorithm. Note that the Neville algorithm performs very badly on equidistant points. If you need to interpolate a polynomial on equidistant points, we recommend to use the barycentric algorithm instead.
 * *Linear Spline*
 * *Cubic Spline* with boundary conditions
 * *Natural Cubic Spline*
 * *Akima Cubic Spline*
+* *Monotone Cubic Spline*: Monotone-preserving piecewise cubic Hermite interpolating polynomial (PCHIP), based on Fritsch & Carlson (1980).
 
 
 Interpolation with additional data
diff --git a/src/Numerics/Interpolation/CubicSpline.cs b/src/Numerics/Interpolation/CubicSpline.cs
index cba2c54c..d2344901 100644
--- a/src/Numerics/Interpolation/CubicSpline.cs
+++ b/src/Numerics/Interpolation/CubicSpline.cs
@@ -216,6 +216,8 @@ namespace MathNet.Numerics.Interpolation
         /// </summary>
         public static CubicSpline InterpolatePchipSorted(double[] x, double[] y)
         {
+            // Implementation based on "Numerical Computing with Matlab" (Moler, 2004).
+
             if (x.Length != y.Length)
             {
                 throw new ArgumentException("All vectors must have the same dimensionality.");