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Commons Math example source code file (

This example Commons Math source code file ( is included in the "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Java - Commons Math tags/keywords

multiplelinearregression, multiplelinearregression

The Commons Math source code

 * 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
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * See the License for the specific language governing permissions and
 * limitations under the License.
package org.apache.commons.math.stat.regression;

 * The multiple linear regression can be represented in matrix-notation.
 * <pre>
 *  y=X*b+u
 * </pre>
 * where y is an <code>n-vector regressand, X is a [n,k] matrix whose k columns are called
 * <b>regressors, b is k-vector of regression parameters and u is an n-vector
 * of <b>error terms or residuals.
 * The notation is quite standard in literature,
 * cf eg <a href="">Davidson and MacKinnon, Econometrics Theory and Methods, 2004.
 * @version $Revision: 811685 $ $Date: 2009-09-05 13:36:48 -0400 (Sat, 05 Sep 2009) $
 * @since 2.0
public interface MultipleLinearRegression {

     * Estimates the regression parameters b.
     * @return The [k,1] array representing b
    double[] estimateRegressionParameters();

     * Estimates the variance of the regression parameters, ie Var(b).
     * @return The [k,k] array representing the variance of b
    double[][] estimateRegressionParametersVariance();

     * Estimates the residuals, ie u = y - X*b.
     * @return The [n,1] array representing the residuals
    double[] estimateResiduals();

     * Returns the variance of the regressand, ie Var(y).
     * @return The double representing the variance of y
    double estimateRegressandVariance();

     * Returns the standard errors of the regression parameters.
     * @return standard errors of estimated regression parameters
     double[] estimateRegressionParametersStandardErrors();


Other Commons Math examples (source code examples)

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