001 /* 002 * Licensed to the Apache Software Foundation (ASF) under one or more 003 * contributor license agreements. See the NOTICE file distributed with 004 * this work for additional information regarding copyright ownership. 005 * The ASF licenses this file to You under the Apache License, Version 2.0 006 * (the "License"); you may not use this file except in compliance with 007 * the License. You may obtain a copy of the License at 008 * 009 * http://www.apache.org/licenses/LICENSE-2.0 010 * 011 * Unless required by applicable law or agreed to in writing, software 012 * distributed under the License is distributed on an "AS IS" BASIS, 013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 014 * See the License for the specific language governing permissions and 015 * limitations under the License. 016 */ 017 package org.apache.commons.math3.stat.regression; 018 019 import org.apache.commons.math3.exception.MathIllegalArgumentException; 020 import org.apache.commons.math3.exception.NoDataException; 021 022 /** 023 * An interface for regression models allowing for dynamic updating of the data. 024 * That is, the entire data set need not be loaded into memory. As observations 025 * become available, they can be added to the regression model and an updated 026 * estimate regression statistics can be calculated. 027 * 028 * @version $Id: UpdatingMultipleLinearRegression.java 1392342 2012-10-01 14:08:52Z psteitz $ 029 * @since 3.0 030 */ 031 public interface UpdatingMultipleLinearRegression { 032 033 /** 034 * Returns true if a constant has been included false otherwise. 035 * 036 * @return true if constant exists, false otherwise 037 */ 038 boolean hasIntercept(); 039 040 /** 041 * Returns the number of observations added to the regression model. 042 * 043 * @return Number of observations 044 */ 045 long getN(); 046 047 /** 048 * Adds one observation to the regression model. 049 * 050 * @param x the independent variables which form the design matrix 051 * @param y the dependent or response variable 052 * @throws ModelSpecificationException if the length of {@code x} does not equal 053 * the number of independent variables in the model 054 */ 055 void addObservation(double[] x, double y) throws ModelSpecificationException; 056 057 /** 058 * Adds a series of observations to the regression model. The lengths of 059 * x and y must be the same and x must be rectangular. 060 * 061 * @param x a series of observations on the independent variables 062 * @param y a series of observations on the dependent variable 063 * The length of x and y must be the same 064 * @throws ModelSpecificationException if {@code x} is not rectangular, does not match 065 * the length of {@code y} or does not contain sufficient data to estimate the model 066 */ 067 void addObservations(double[][] x, double[] y) throws ModelSpecificationException; 068 069 /** 070 * Clears internal buffers and resets the regression model. This means all 071 * data and derived values are initialized 072 */ 073 void clear(); 074 075 076 /** 077 * Performs a regression on data present in buffers and outputs a RegressionResults object 078 * @return RegressionResults acts as a container of regression output 079 * @throws ModelSpecificationException if the model is not correctly specified 080 * @throws NoDataException if there is not sufficient data in the model to 081 * estimate the regression parameters 082 */ 083 RegressionResults regress() throws ModelSpecificationException, NoDataException; 084 085 /** 086 * Performs a regression on data present in buffers including only regressors 087 * indexed in variablesToInclude and outputs a RegressionResults object 088 * @param variablesToInclude an array of indices of regressors to include 089 * @return RegressionResults acts as a container of regression output 090 * @throws ModelSpecificationException if the model is not correctly specified 091 * @throws MathIllegalArgumentException if the variablesToInclude array is null or zero length 092 */ 093 RegressionResults regress(int[] variablesToInclude) throws ModelSpecificationException, MathIllegalArgumentException; 094 }