////  OpenForecast - open source, general-purpose forecasting package.//  Copyright (C) 2002  Steven R. Gould////  This library is free software; you can redistribute it and/or//  modify it under the terms of the GNU Lesser General Public//  License as published by the Free Software Foundation; either//  version 2.1 of the License, or (at your option) any later version.////  This library is distributed in the hope that it will be useful,//  but WITHOUT ANY WARRANTY; without even the implied warranty of//  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU//  Lesser General Public License for more details.////  You should have received a copy of the GNU Lesser General Public//  License along with this library; if not, write to the Free Software//  Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA//package net.sourceforge.openforecast.models;/** * A simple Java Bean that gathers together in one class all current "accuracy * indicators" for a given forecasting model. Currently, the supported * measurements of accuracy of a forecasting model supported by this class * include: * <ul> *  <li>bias - or the mean error</li> *  <li>MAD - or the Mean Absolute Deviation</li> *  <li>MAPE - or the Mean Absolute Percentage Error</li> *  <li>MSE - or the Mean Square of the Error</li> *  <li>SAE - or the Sum of the Absolute Errors</li> * </ul> * @since 0.3 * @author Steven R. Gould */class AccuracyIndicators{	/** Arithmetic mean of the errors. */	private double bias;		/** Mean Absolute Deviation. */	private double mad;	/** Mean Absolute Percentage Error. */	private double mape;	/** Mean Square of the Error. */	private double mse;	/** Sum of the Absolute Errors. */	private double sae;	/**	 * Default constructor. Initializes all accuracy indicators to their	 * "worst" possible values - generally this means some large number,	 * indicating "very" inaccurate.	 */	public AccuracyIndicators()	{		bias = mad = mape = mse = sae = Double.MAX_VALUE;	}	/**	 * Returns the bias for the associated forecasting model.	 * @return the bias.	 */	public double getBias()	{		return bias;	}	/**	 * Sets the bias for the associated forecasting model to the given value.	 * @param bias the new value for the bias.	 */	public void setBias(double bias)	{		this.bias = bias;	}	/**	 * Returns the Mean Absolute Deviation (MAD) for the associated	 * forecasting model to the given value.	 * @return the Mean Absolute Deviation.	 */	public double getMAD()	{		return mad;	}	/**	 * Sets the Mean Absolute Deviation (MAD) for the associated forecasting	 * model. That is, the <code>SUM( abs(actual-forecast) ) / n</code> for	 * the initial data set.	 * @param mad the new value for the Mean Absolute Deviation.	 */	public void setMAD(double mad)	{		this.mad = mad;	}	/**	 * Returns the Mean Absolute Percentage Error (MAPE) for the associated	 * forecasting model. That is, the	 * <code>SUM( 100% . abs(actual-forecast)/actual ) / n</code> for the	 * initial data set.	 * @return the Mean Absolute Percentage Error.	 */	public double getMAPE()	{		return mape;	}	/**	 * Sets the Mean Absolute Percentage Error (MAPE) for the associated	 * forecasting model to the given value.	 * @param mape the new value for the Mean Absolute Percentage Error.	 */	public void setMAPE(double mape)	{		this.mape = mape;	}	/**	 * Returns the Mean Square of the Errors (MSE) for the associated	 * forecasting model. That is, the	 * <code>SUM( (actual-forecast)^2 ) / n</code> for the initial data set.	 * @return the Mean Square of the Errors.	 */	public double getMSE()	{		return mse;	}	/**	 * Sets the Mean Square of the Errors (MSE) for the associated	 * forecasting model to the new value.	 * @param mse the new value for the Mean Square of the Errors.	 */	public void setMSE(double mse)	{		this.mse = mse;	}	/**	 * Returns the Sum of the Absolute Errors (SAE) for the associated	 * forecasting model. That is, the	 * <code>SUM( abs(actual-forecast) )</code> for the initial data set.	 * @return the Mean Absolute Deviation.	 */	public double getSAE()	{		return sae;	}	/**	 * Sets the Sum of the Absolute Errors (SAE) for the associated	 * forecasting model to the new value.	 * @return the new value for the Mean Absolute Deviation.	 */	public void setSAE(double sae)	{		this.sae = sae;	}	/**	 * Returns a string containing the accuracy indicators and their values.	 * Overridden to provide some useful output for debugging.	 * @return a string containing the accuracy indicators and their values.	 */	public String toString()	{		return "bias=" + bias			+ ", MAD=" + mad			+ ", MAPE=" + mape			+ ", MSE=" + mse			+ ", sae=" + sae;	}}