code: //==============================================================================
  //	
  //	Copyright (c) 2002-
  //	Authors:
  //	* Vincent Nimal <vincent.nimal@comlab.ox.ac.uk> (University of Oxford)
  //	* Dave Parker <david.parker@comlab.ox.ac.uk> (University of Oxford)
  //	
  //------------------------------------------------------------------------------
  //	
  //	This file is part of PRISM.
  //	
  //	PRISM is free software; you can redistribute it and/or modify
  //	it under the terms of the GNU General Public License as published by
  //	the Free Software Foundation; either version 2 of the License, or
  //	(at your option) any later version.
  //	
  //	PRISM 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 General Public License for more details.
  //	
  //	You should have received a copy of the GNU General Public License
  //	along with PRISM; if not, write to the Free Software Foundation,
  //	Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
  //	
  //==============================================================================
  
  package simulator.method;
  
  import prism.PrismException;
  import simulator.sampler.Sampler;
  import cern.jet.stat.Probability;
  
  /**
   * SimulationMethod class for the CI ("confidence interval") approach.
   * Case where 'width' is unknown parameter.
   */
  public final class CIwidth extends CIMethod
  {
  	// Estimate of variance (from sampling)
  	private double varEstimator;
  
  	public CIwidth(double confidenceLevel, int iterations)
  	{
  		this.confidence = confidenceLevel;
  		this.numSamples = iterations;
  		varEstimator = 0.0;
  	}
  
  	@Override
  	public void computeMissingParameterAfterSim()
  	{
  		double quantile;
  		// Only compute for numSamples > 1
  		// (Student's t-distribution only defined for v > 0)
  		if (numSamples > 1) {
  			// (Note: Colt's studentTinverse seems to break for v=1 so do manually)
  			if (numSamples - 1 > 1) {
  				quantile = Probability.studentTInverse(confidence, numSamples - 1);
  			} else {
  				// PDF for v=1 is 1/2 + arctan(x)/pi
  				// Want x for pdf = 1-conf/2 
  				quantile = Math.tan((0.5 - confidence / 2) * Math.PI);
  			}
  			width = quantile * Math.sqrt(varEstimator / numSamples);
  			missingParameterComputed = true;
  		}
  	}
  
  	@Override
  	public Object getMissingParameter() throws PrismException
  	{
  		if (!missingParameterComputed)
  			throw new PrismException("Missing parameter not computed yet");
  		return width;
  	}
  
  	@Override
  	public String getParametersString()
  	{
  		if (!missingParameterComputed)
  			return "width=" + "unknown" + ", confidence=" + confidence + ", number of samples=" + numSamples;
  		else
  			return "width=" + width + ", confidence=" + confidence + ", number of samples=" + numSamples;
  	}
  
  	@Override
  	public boolean shouldStopNow(int iters, Sampler sampler)
  	{
  		if (iters >= numSamples) {
  			// Store final variance for confidence computation later
  			varEstimator = sampler.getVariance();
  			return true;
  		}
  		return false;
  	}
  
  	@Override
  	public int getProgress(int iters, Sampler sampler)
  	{
  		// Easy: percentage of iters done so far
  		return ((10 * iters) / numSamples) * 10;
  	}
  
  	@Override
  	public Object getResult(Sampler sampler) throws PrismException
  	{
  		// We may use 'width' to compute the result, so compute if necessary
  		// (this should never happen)
  		if (!missingParameterComputed)
  			computeMissingParameterAfterSim();
  		return super.getResult(sampler);
  	}
  
  	@Override
  	public String getResultExplanation(Sampler sampler) throws PrismException
  	{
  		// We may use 'width' to compute the result, so compute if necessary
  		// (this should never happen)
  		if (!missingParameterComputed)
  			computeMissingParameterAfterSim();
  		return super.getResultExplanation(sampler);
  	}
  
  	@Override
  	public SimulationMethod clone()
  	{
  		CIwidth m = new CIwidth(confidence, numSamples);
  		// Remaining CIMethod stuff
  		m.width = width;
  		m.missingParameterComputed = missingParameterComputed;
  		m.prOp = prOp;
  		m.theta = theta;
  		// Local stuff
  		m.varEstimator = varEstimator;
  		return m;
  	}
  }
  