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Time series observations with different forecasting models
Source code name: "ForecastingChartDemo.java"
Programming language: Java
Topic: Finance/Forecasts
DMelt Version 2.4. Last modified: 02/01/1973. License: Pro
https://datamelt.org/code/cache/ForecastingChartDemo_6203.java
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//
// OpenForecast - open source, general-purpose forecasting package.
// Copyright (C) 2002-2004 Steven R. Gould. GNU public license
//
import java.util.Date;
import java.util.Iterator;
import org.jfree.chart.ChartFactory;
import org.jfree.chart.ChartPanel;
import org.jfree.chart.JFreeChart;
import org.jfree.chart.renderer.xy.StandardXYItemRenderer;
import org.jfree.chart.renderer.xy.XYItemRenderer;
import org.jfree.chart.plot.XYPlot;
import org.jfree.data.time.TimeSeries;
import org.jfree.data.time.Quarter;
import org.jfree.data.time.TimeSeriesDataItem;
import org.jfree.data.xy.XYDataset;
import org.jfree.data.time.TimeSeriesCollection;
import org.jfree.ui.ApplicationFrame;
import net.sourceforge.openforecast.DataPoint;
import net.sourceforge.openforecast.DataSet;
import net.sourceforge.openforecast.Forecaster;
import net.sourceforge.openforecast.ForecastingModel;
import net.sourceforge.openforecast.Observation;
import net.sourceforge.openforecast.models.MovingAverageModel;
import net.sourceforge.openforecast.models.NaiveForecastingModel;
import net.sourceforge.openforecast.models.RegressionModel;
import net.sourceforge.openforecast.models.PolynomialRegressionModel;
/**
* An example of a time series chart, showing an initial series of
* observations (the first data series), overlaid with forecasts produced
* using a variety of different forecasting models. This both demonstrates
* the use of JFreeChart, as well as provides a graphical comparison of
* some of the different forecasting models.
*/
public class ForecastingChartDemo extends ApplicationFrame
{
/** The set of data points for which forecast values are required. */
private TimeSeries fc;
/**
* A demonstration application showing a quarterly time series
* along with the forecast values.
* @param title the frame title.
*/
public ForecastingChartDemo(String title)
{
super(title);
// Create a title...
String chartTitle = "Different forecasting models";
XYDataset dataset = createDataset();
JFreeChart chart
= ChartFactory.createTimeSeriesChart(chartTitle,
"Date",
"Quarterly Sales (Units sold)",
dataset,
true, // Legend
true, // Tooltips
false);// URLs
XYPlot plot = chart.getXYPlot();
XYItemRenderer renderer = plot.getRenderer();
if (renderer instanceof StandardXYItemRenderer)
{
StandardXYItemRenderer r = (StandardXYItemRenderer) renderer;
// r.setPlotShapes(true);
// r.setDefaultShapesFilled(Boolean.TRUE);
}
ChartPanel chartPanel = new ChartPanel(chart);
chartPanel.setPreferredSize(new java.awt.Dimension(600, 500));
setContentPane(chartPanel);
}
/**
* Creates a dataset, consisting of two series of monthly data.
* @return the dataset.
*/
public XYDataset createDataset()
{
TimeSeries observations
= new TimeSeries("Quarterly Sales", Quarter.class);
observations.add(new Quarter(1,1990), 362.0);
observations.add(new Quarter(2,1990), 385.0);
observations.add(new Quarter(3,1990), 432.0);
observations.add(new Quarter(4,1990), 341.0);
observations.add(new Quarter(1,1991), 382.0);
observations.add(new Quarter(2,1991), 409.0);
observations.add(new Quarter(3,1991), 498.0);
observations.add(new Quarter(4,1991), 387.0);
observations.add(new Quarter(1,1992), 473.0);
observations.add(new Quarter(2,1992), 513.0);
observations.add(new Quarter(3,1992), 582.0);
observations.add(new Quarter(4,1992), 474.0);
observations.add(new Quarter(1,1993), 544.0);
observations.add(new Quarter(2,1993), 582.0);
observations.add(new Quarter(3,1993), 681.0);
observations.add(new Quarter(4,1993), 557.0);
observations.add(new Quarter(1,1994), 628.0);
observations.add(new Quarter(2,1994), 707.0);
observations.add(new Quarter(3,1994), 773.0);
observations.add(new Quarter(4,1994), 592.0);
observations.add(new Quarter(1,1995), 627.0);
observations.add(new Quarter(2,1995), 725.0);
observations.add(new Quarter(3,1995), 854.0);
observations.add(new Quarter(4,1995), 661.0);
fc = new TimeSeries("Forecast values", Quarter.class);
fc.add(new Quarter(1,1990), 0.0);
fc.add(new Quarter(2,1990), 0.0);
fc.add(new Quarter(3,1990), 0.0);
fc.add(new Quarter(4,1990), 0.0);
fc.add(new Quarter(1,1991), 0.0);
fc.add(new Quarter(2,1991), 0.0);
fc.add(new Quarter(3,1991), 0.0);
fc.add(new Quarter(4,1991), 0.0);
fc.add(new Quarter(1,1992), 0.0);
fc.add(new Quarter(2,1992), 0.0);
fc.add(new Quarter(3,1992), 0.0);
fc.add(new Quarter(4,1992), 0.0);
fc.add(new Quarter(1,1993), 0.0);
fc.add(new Quarter(2,1993), 0.0);
fc.add(new Quarter(3,1993), 0.0);
fc.add(new Quarter(4,1993), 0.0);
fc.add(new Quarter(1,1994), 0.0);
fc.add(new Quarter(2,1994), 0.0);
fc.add(new Quarter(3,1994), 0.0);
fc.add(new Quarter(4,1994), 0.0);
fc.add(new Quarter(1,1995), 0.0);
fc.add(new Quarter(2,1995), 0.0);
fc.add(new Quarter(3,1995), 0.0);
fc.add(new Quarter(4,1995), 0.0);
fc.add(new Quarter(1,1996), 0.0);
fc.add(new Quarter(2,1996), 0.0);
fc.add(new Quarter(3,1996), 0.0);
fc.add(new Quarter(4,1996), 0.0);
fc.add(new Quarter(1,1997), 0.0);
fc.add(new Quarter(2,1997), 0.0);
fc.add(new Quarter(3,1997), 0.0);
fc.add(new Quarter(4,1997), 0.0);
fc.add(new Quarter(1,1998), 0.0);
fc.add(new Quarter(2,1998), 0.0);
fc.add(new Quarter(3,1998), 0.0);
fc.add(new Quarter(4,1998), 0.0);
DataSet initDataSet = getDataSet( observations, 0, 100 );
TimeSeries naiveSeries
= getForecastTimeSeries(new NaiveForecastingModel(),
initDataSet,
1, 25,
"Naive forecast");
TimeSeries ma4Series
= getForecastTimeSeries(new MovingAverageModel(4),
initDataSet,
4, 28,
"4 Period Moving Average");
TimeSeries ma8Series
= getForecastTimeSeries(new MovingAverageModel(8),
initDataSet,
8, 32,
"8 Period Moving Average");
TimeSeries regressionSeries
= getForecastTimeSeries(new RegressionModel("t"),
initDataSet,
0, 100,
"Linear regression");
TimeSeries polyRegressSeries
= getForecastTimeSeries(new PolynomialRegressionModel("t",4),
initDataSet,
0, 100,
"4th order polynomial regression");
TimeSeriesCollection dataset = new TimeSeriesCollection();
dataset.addSeries(observations);
dataset.addSeries(naiveSeries);
dataset.addSeries(ma4Series);
dataset.addSeries(ma8Series);
dataset.addSeries(regressionSeries);
dataset.addSeries(polyRegressSeries);
return dataset;
}
/**
* A helper function to convert data points (from startIndex to
* endIndex) of a (JFreeChart) TimeSeries object into an
* OpenForecast DataSet.
* @param series the series of data points stored as a JFreeChart
* TimeSeries object.
* @param startIndex the index of the first data point required from the
* series.
* @param endIndex the index of the last data point required from the
* series.
* @return an OpenForecast DataSet representing the data points extracted
* from the TimeSeries.
*/
private DataSet getDataSet( TimeSeries series,
int startIndex, int endIndex )
{
DataSet dataSet = new DataSet();
if ( endIndex > series.getItemCount() )
endIndex = series.getItemCount();
for ( int i=startIndex; i
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