Fit: F# Fit.multiDim

src/FSharp/Fit.fs

@@ -47,6 +47,13 @@ module Fit =
     /// returning a function y' for the best fitting line.
     let lineFunc x y = Fit.LineFunc(x,y) |> tofs
 
+    /// Least-Squares fitting the points ((x0,x1,...,xk),y) to a linear surface y : X -> p0*x0 + p1*x1 + ... + pk*xk,
+    /// returning its best fitting parameters as [p0, p1, p2, ..., pk] array.
+    let multiDim intercept x y = Fit.MultiDim(x,y,intercept)
+
+    /// Least-Squares fitting the points ((x0,x1,...,xk),y) to a linear surface y : X -> p0*x0 + p1*x1 + ... + pk*xk,
+    /// returning a function y' for the best fitting surface.
+    let multiDimFunc intercept x y = Fit.MultiDimFunc(x,y,intercept) |> tofs
 
     /// Least-Squares fitting the points (x,y) to a k-order polynomial y : x -> p0 + p1*x + p2*x^2 + ... + pk*x^k,
     /// returning its best fitting parameters as [p0, p1, p2, ..., pk] array, compatible with Evaluate.Polynomial.
@@ -56,7 +63,6 @@ module Fit =
     /// returning a function y' for the best fitting polynomial.
     let polynomialFunc order x y = Fit.PolynomialFunc(x,y,order) |> tofs
 
-
     /// Least-Squares fitting the points (x,y) to an arbitrary linear combination y : x -> p0*f0(x) + p1*f1(x) + ... + pk*fk(x),
     /// returning its best fitting parameters as [p0, p1, p2, ..., pk] list.
     let linear functions (x:_[]) (y:float[]) =