

Java example source code file (UpdatingMultipleLinearRegression.java)
The UpdatingMultipleLinearRegression.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/LICENSE2.0 * * 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.stat.regression; import org.apache.commons.math3.exception.MathIllegalArgumentException; import org.apache.commons.math3.exception.NoDataException; /** * An interface for regression models allowing for dynamic updating of the data. * That is, the entire data set need not be loaded into memory. As observations * become available, they can be added to the regression model and an updated * estimate regression statistics can be calculated. * * @since 3.0 */ public interface UpdatingMultipleLinearRegression { /** * Returns true if a constant has been included false otherwise. * * @return true if constant exists, false otherwise */ boolean hasIntercept(); /** * Returns the number of observations added to the regression model. * * @return Number of observations */ long getN(); /** * Adds one observation to the regression model. * * @param x the independent variables which form the design matrix * @param y the dependent or response variable * @throws ModelSpecificationException if the length of {@code x} does not equal * the number of independent variables in the model */ void addObservation(double[] x, double y) throws ModelSpecificationException; /** * Adds a series of observations to the regression model. The lengths of * x and y must be the same and x must be rectangular. * * @param x a series of observations on the independent variables * @param y a series of observations on the dependent variable * The length of x and y must be the same * @throws ModelSpecificationException if {@code x} is not rectangular, does not match * the length of {@code y} or does not contain sufficient data to estimate the model */ void addObservations(double[][] x, double[] y) throws ModelSpecificationException; /** * Clears internal buffers and resets the regression model. This means all * data and derived values are initialized */ void clear(); /** * Performs a regression on data present in buffers and outputs a RegressionResults object * @return RegressionResults acts as a container of regression output * @throws ModelSpecificationException if the model is not correctly specified * @throws NoDataException if there is not sufficient data in the model to * estimate the regression parameters */ RegressionResults regress() throws ModelSpecificationException, NoDataException; /** * Performs a regression on data present in buffers including only regressors * indexed in variablesToInclude and outputs a RegressionResults object * @param variablesToInclude an array of indices of regressors to include * @return RegressionResults acts as a container of regression output * @throws ModelSpecificationException if the model is not correctly specified * @throws MathIllegalArgumentException if the variablesToInclude array is null or zero length */ RegressionResults regress(int[] variablesToInclude) throws ModelSpecificationException, MathIllegalArgumentException; } Other Java examples (source code examples)Here is a short list of links related to this Java UpdatingMultipleLinearRegression.java source code file: 
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