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diff --git a/src/main/java/org/apache/commons/math3/analysis/interpolation/DividedDifferenceInterpolator.java b/src/main/java/org/apache/commons/math3/analysis/interpolation/DividedDifferenceInterpolator.java
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+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.commons.math3.analysis.interpolation;
+
+import java.io.Serializable;
+import org.apache.commons.math3.analysis.polynomials.PolynomialFunctionLagrangeForm;
+import org.apache.commons.math3.analysis.polynomials.PolynomialFunctionNewtonForm;
+import org.apache.commons.math3.exception.DimensionMismatchException;
+import org.apache.commons.math3.exception.NumberIsTooSmallException;
+import org.apache.commons.math3.exception.NonMonotonicSequenceException;
+
+/**
+ * Implements the <a href=
+ * "http://mathworld.wolfram.com/NewtonsDividedDifferenceInterpolationFormula.html">
+ * Divided Difference Algorithm</a> for interpolation of real univariate
+ * functions. For reference, see <b>Introduction to Numerical Analysis</b>,
+ * ISBN 038795452X, chapter 2.
+ * <p>
+ * The actual code of Neville's evaluation is in PolynomialFunctionLagrangeForm,
+ * this class provides an easy-to-use interface to it.</p>
+ *
+ * @since 1.2
+ */
+public class DividedDifferenceInterpolator
+    implements UnivariateInterpolator, Serializable {
+    /** serializable version identifier */
+    private static final long serialVersionUID = 107049519551235069L;
+
+    /**
+     * Compute an interpolating function for the dataset.
+     *
+     * @param x Interpolating points array.
+     * @param y Interpolating values array.
+     * @return a function which interpolates the dataset.
+     * @throws DimensionMismatchException if the array lengths are different.
+     * @throws NumberIsTooSmallException if the number of points is less than 2.
+     * @throws NonMonotonicSequenceException if {@code x} is not sorted in
+     * strictly increasing order.
+     */
+    public PolynomialFunctionNewtonForm interpolate(double x[], double y[])
+        throws DimensionMismatchException,
+               NumberIsTooSmallException,
+               NonMonotonicSequenceException {
+        /**
+         * a[] and c[] are defined in the general formula of Newton form:
+         * p(x) = a[0] + a[1](x-c[0]) + a[2](x-c[0])(x-c[1]) + ... +
+         *        a[n](x-c[0])(x-c[1])...(x-c[n-1])
+         */
+        PolynomialFunctionLagrangeForm.verifyInterpolationArray(x, y, true);
+
+        /**
+         * When used for interpolation, the Newton form formula becomes
+         * p(x) = f[x0] + f[x0,x1](x-x0) + f[x0,x1,x2](x-x0)(x-x1) + ... +
+         *        f[x0,x1,...,x[n-1]](x-x0)(x-x1)...(x-x[n-2])
+         * Therefore, a[k] = f[x0,x1,...,xk], c[k] = x[k].
+         * <p>
+         * Note x[], y[], a[] have the same length but c[]'s size is one less.</p>
+         */
+        final double[] c = new double[x.length-1];
+        System.arraycopy(x, 0, c, 0, c.length);
+
+        final double[] a = computeDividedDifference(x, y);
+        return new PolynomialFunctionNewtonForm(a, c);
+    }
+
+    /**
+     * Return a copy of the divided difference array.
+     * <p>
+     * The divided difference array is defined recursively by <pre>
+     * f[x0] = f(x0)
+     * f[x0,x1,...,xk] = (f[x1,...,xk] - f[x0,...,x[k-1]]) / (xk - x0)
+     * </pre>
+     * <p>
+     * The computational complexity is \(O(n^2)\) where \(n\) is the common
+     * length of {@code x} and {@code y}.</p>
+     *
+     * @param x Interpolating points array.
+     * @param y Interpolating values array.
+     * @return a fresh copy of the divided difference array.
+     * @throws DimensionMismatchException if the array lengths are different.
+     * @throws NumberIsTooSmallException if the number of points is less than 2.
+     * @throws NonMonotonicSequenceException
+     * if {@code x} is not sorted in strictly increasing order.
+     */
+    protected static double[] computeDividedDifference(final double x[], final double y[])
+        throws DimensionMismatchException,
+               NumberIsTooSmallException,
+               NonMonotonicSequenceException {
+        PolynomialFunctionLagrangeForm.verifyInterpolationArray(x, y, true);
+
+        final double[] divdiff = y.clone(); // initialization
+
+        final int n = x.length;
+        final double[] a = new double [n];
+        a[0] = divdiff[0];
+        for (int i = 1; i < n; i++) {
+            for (int j = 0; j < n-i; j++) {
+                final double denominator = x[j+i] - x[j];
+                divdiff[j] = (divdiff[j+1] - divdiff[j]) / denominator;
+            }
+            a[i] = divdiff[0];
+        }
+
+        return a;
+    }
+}