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Java example source code file (MultipleLinearRegression.java)

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

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The MultipleLinearRegression.java Java example 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
 *      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,
 * See the License for the specific language governing permissions and
 * limitations under the License.
package org.apache.commons.math3.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="http://www.econ.queensu.ca/ETM">Davidson and MacKinnon, Econometrics Theory and Methods, 2004.
 * @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();


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