* Removed the dependency on the flanagan library. It is now replaced with Apache Math.

* The minimal time between events is now configurable

modules/cloudsim/scripts/install-flanagan.sh

-#!/bin/sh
-wget http://www.ee.ucl.ac.uk/~mflanaga/java/flanagan.jar
-mvn install:install-file -DgroupId=org.flanagan -DartifactId=flanagan -Dversion=1.0 -Dfile=flanagan.jar -Dpackaging=jar -DgeneratePom=true
-rm flanagan.jar

modules/cloudsim/src/main/java/org/cloudbus/cloudsim/CloudletSchedulerDynamicWorkload.java

@@ -12,6 +12,8 @@ import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
 
+import org.cloudbus.cloudsim.core.CloudSim;
+
 /**
  * CloudletSchedulerDynamicWorkload implements a policy of scheduling performed by a virtual machine
  * assuming that there is just one cloudlet which is working as an online service.
@@ -81,8 +83,8 @@ public class CloudletSchedulerDynamicWorkload extends CloudletSchedulerTimeShare
 				continue;
 			} else { // not finish: estimate the finish time
 				double estimatedFinishTime = getEstimatedFinishTime(rcl, currentTime);
-				if (estimatedFinishTime - currentTime < 0.1) {
-					estimatedFinishTime = currentTime + 0.1;
+				if (estimatedFinishTime - currentTime < CloudSim.getMinTimeBetweenEvents()) {
+					estimatedFinishTime = currentTime + CloudSim.getMinTimeBetweenEvents();
 				}
 				if (estimatedFinishTime < nextEvent) {
 					nextEvent = estimatedFinishTime;

modules/cloudsim/src/main/java/org/cloudbus/cloudsim/CloudletSchedulerSpaceShared.java

@@ -136,8 +136,8 @@ public class CloudletSchedulerSpaceShared extends CloudletScheduler {
 		for (ResCloudlet rcl : getCloudletExecList()) {
 			double remainingLength = rcl.getRemainingCloudletLength();
 			double estimatedFinishTime = currentTime + (remainingLength / (capacity * rcl.getNumberOfPes()));
-			if (estimatedFinishTime - currentTime < 0.1) {
-				estimatedFinishTime = currentTime + 0.1;
+			if (estimatedFinishTime - currentTime < CloudSim.getMinTimeBetweenEvents()) {
+				estimatedFinishTime = currentTime + CloudSim.getMinTimeBetweenEvents();
 			}
 			if (estimatedFinishTime < nextEvent) {
 				nextEvent = estimatedFinishTime;

modules/cloudsim/src/main/java/org/cloudbus/cloudsim/CloudletSchedulerTimeShared.java

@@ -90,8 +90,8 @@ public class CloudletSchedulerTimeShared extends CloudletScheduler {
 		for (ResCloudlet rcl : getCloudletExecList()) {
 			double estimatedFinishTime = currentTime
 					+ (rcl.getRemainingCloudletLength() / (getCapacity(mipsShare) * rcl.getNumberOfPes()));
-			if (estimatedFinishTime - currentTime < 0.1) {
-				estimatedFinishTime = currentTime + 0.1;
+			if (estimatedFinishTime - currentTime < CloudSim.getMinTimeBetweenEvents()) {
+				estimatedFinishTime = currentTime + CloudSim.getMinTimeBetweenEvents();
 			}
 
 			if (estimatedFinishTime < nextEvent) {

modules/cloudsim/src/main/java/org/cloudbus/cloudsim/Datacenter.java

@@ -440,7 +440,7 @@ public class Datacenter extends SimEntity {
 			} else {
 				data[2] = CloudSimTags.FALSE;
 			}
-			send(vm.getUserId(), 0.1, CloudSimTags.VM_CREATE_ACK, data);
+			send(vm.getUserId(), CloudSim.getMinTimeBetweenEvents(), CloudSimTags.VM_CREATE_ACK, data);
 		}
 
 		if (result) {
@@ -866,7 +866,7 @@ public class Datacenter extends SimEntity {
 		// if some time passed since last processing
 		// R: for term is to allow loop at simulation start. Otherwise, one initial
 		// simulation step is skipped and schedulers are not properly initialized
-		if (CloudSim.clock() < 0.111 || CloudSim.clock() > getLastProcessTime() + 0.1) {
+		if (CloudSim.clock() < 0.111 || CloudSim.clock() > getLastProcessTime() + CloudSim.getMinTimeBetweenEvents()) {
 			List<? extends Host> list = getVmAllocationPolicy().getHostList();
 			double smallerTime = Double.MAX_VALUE;
 			// for each host...
@@ -880,8 +880,8 @@ public class Datacenter extends SimEntity {
 				}
 			}
 			// gurantees a minimal interval before scheduling the event
-			if (smallerTime < CloudSim.clock() + 0.11) {
-				smallerTime = CloudSim.clock() + 0.11;
+			if (smallerTime < CloudSim.clock() + CloudSim.getMinTimeBetweenEvents() + 0.01) {
+				smallerTime = CloudSim.clock() + CloudSim.getMinTimeBetweenEvents() + 0.01;
 			}
 			if (smallerTime != Double.MAX_VALUE) {
 				schedule(getId(), (smallerTime - CloudSim.clock()), CloudSimTags.VM_DATACENTER_EVENT);

modules/cloudsim/src/main/java/org/cloudbus/cloudsim/core/CloudSim.java

@@ -62,6 +62,9 @@ public class CloudSim {
 	/** The termination time. */
 	private static double terminateAt = -1;
 
+	/** The minimal time between events. Events within shorter periods after the last event are discarded. */
+	private static double minTimeBetweenEvents = 0.1;
+	
 	/**
 	 * Initialises all the common attributes.
 	 * 
@@ -131,6 +134,40 @@ public class CloudSim {
 		}
 	}
 
+	/**
+	 * Initialises CloudSim parameters. This method should be called before creating any entities.
+	 * <p>
+	 * Inside this method, it will create the following CloudSim entities:
+	 * <ul>
+	 * <li>CloudInformationService.
+	 * <li>CloudSimShutdown
+	 * </ul>
+	 * <p>
+	 * 
+	 * @param numUser the number of User Entities created. This parameters indicates that
+	 *            {@link gridsim.CloudSimShutdown} first waits for all user entities's
+	 *            END_OF_SIMULATION signal before issuing terminate signal to other entities
+	 * @param cal starting time for this simulation. If it is <tt>null</tt>, then the time will be
+	 *            taken from <tt>Calendar.getInstance()</tt>
+	 * @param traceFlag <tt>true</tt> if CloudSim trace need to be written
+	 * @param periodBetweenEvents - the minimal period between events. Events within shorter periods
+	 * after the last event are discarded.
+	 * @see gridsim.CloudSimShutdown
+	 * @see CloudInformationService.CloudInformationService
+	 * @pre numUser >= 0
+	 * @post $none
+	 */
+	public static void init(int numUser, Calendar cal, boolean traceFlag, double periodBetweenEvents) {
+	    if (periodBetweenEvents <= 0) {
+		throw new IllegalArgumentException("The minimal time between events should be positive, but is:" + periodBetweenEvents);
+	    }
+	    
+	    init(numUser, cal, traceFlag);
+	    minTimeBetweenEvents = periodBetweenEvents;
+	}
+	
+	
+	
 	/**
 	 * Starts the execution of CloudSim simulation. It waits for complete execution of all entities,
 	 * i.e. until all entities threads reach non-RUNNABLE state or there are no more events in the
@@ -212,6 +249,15 @@ public class CloudSim {
 		return true;
 	}
 
+	
+	/**
+	 * Returns the minimum time between events. Events within shorter periods after the last event are discarded. 
+	 * @return the minimum time between events.
+	 */
+	public static double getMinTimeBetweenEvents() {
+	    return minTimeBetweenEvents;
+	}
+
 	/**
 	 * Gets a new copy of initial simulation Calendar.
 	 * 

modules/cloudsim/src/main/java/org/cloudbus/cloudsim/network/datacenter/NetworkCloudletSpaceSharedScheduler.java

@@ -218,8 +218,8 @@ public class NetworkCloudletSpaceSharedScheduler extends CloudletScheduler {
 		for (ResCloudlet rcl : getCloudletExecList()) {
 			double remainingLength = rcl.getRemainingCloudletLength();
 			double estimatedFinishTime = currentTime + (remainingLength / (capacity * rcl.getNumberOfPes()));
-			if (estimatedFinishTime - currentTime < 0.1) {
-				estimatedFinishTime = currentTime + 0.1;
+			if (estimatedFinishTime - currentTime < CloudSim.getMinTimeBetweenEvents()) {
+				estimatedFinishTime = currentTime + CloudSim.getMinTimeBetweenEvents();
 			}
 			if (estimatedFinishTime < nextEvent) {
 				nextEvent = estimatedFinishTime;

modules/cloudsim/src/main/java/org/cloudbus/cloudsim/power/PowerVm.java

@@ -16,8 +16,6 @@ import org.cloudbus.cloudsim.Vm;
 import org.cloudbus.cloudsim.core.CloudSim;
 import org.cloudbus.cloudsim.util.MathUtil;
 
-import flanagan.analysis.Stat;
-
 /**
  * The class of a VM that stores its CPU utilization history. The history is used by VM allocation
  * and selection policies.
@@ -63,17 +61,17 @@ public class PowerVm extends Vm {
 	 * @param schedulingInterval the scheduling interval
 	 */
 	public PowerVm(
-			int id,
-			int userId,
-			double mips,
-			int pesNumber,
-			int ram,
-			long bw,
-			long size,
-			int priority,
-			String vmm,
-			CloudletScheduler cloudletScheduler,
-			double schedulingInterval) {
+			final int id,
+			final int userId,
+			final double mips,
+			final int pesNumber,
+			final int ram,
+			final long bw,
+			final long size,
+			final int priority,
+			final String vmm,
+			final CloudletScheduler cloudletScheduler,
+			final double schedulingInterval) {
 		super(id, userId, mips, pesNumber, ram, bw, size, vmm, cloudletScheduler);
 		setSchedulingInterval(schedulingInterval);
 	}
@@ -85,13 +83,13 @@ public class PowerVm extends Vm {
 	 * @param mipsShare array with MIPS share of each Pe available to the scheduler
 	 * 
 	 * @return time predicted completion time of the earliest finishing cloudlet, or 0 if there is
-	 *         no next events
+	 * 		no next events
 	 * 
 	 * @pre currentTime >= 0
 	 * @post $none
 	 */
 	@Override
-	public double updateVmProcessing(double currentTime, List<Double> mipsShare) {
+	public double updateVmProcessing(final double currentTime, final List<Double> mipsShare) {
 		double time = super.updateVmProcessing(currentTime, mipsShare);
 		if (currentTime > getPreviousTime() && (currentTime - 0.1) % getSchedulingInterval() == 0) {
 			double utilization = getTotalUtilizationOfCpu(getCloudletScheduler().getPreviousTime());
@@ -120,7 +118,7 @@ public class PowerVm extends Vm {
 			for (int i = 0; i < n; i++) {
 				deviationSum[i] = Math.abs(median - getUtilizationHistory().get(i));
 			}
-			mad = Stat.median(deviationSum);
+			mad = MathUtil.median(deviationSum);
 		}
 		return mad;
 	}
@@ -172,7 +170,7 @@ public class PowerVm extends Vm {
 	 * 
 	 * @param utilization the utilization
 	 */
-	public void addUtilizationHistoryValue(double utilization) {
+	public void addUtilizationHistoryValue(final double utilization) {
 		getUtilizationHistory().add(0, utilization);
 		if (getUtilizationHistory().size() > HISTORY_LENGTH) {
 			getUtilizationHistory().remove(HISTORY_LENGTH);
@@ -202,7 +200,7 @@ public class PowerVm extends Vm {
 	 * 
 	 * @param previousTime the new previous time
 	 */
-	public void setPreviousTime(double previousTime) {
+	public void setPreviousTime(final double previousTime) {
 		this.previousTime = previousTime;
 	}
 
@@ -220,7 +218,7 @@ public class PowerVm extends Vm {
 	 * 
 	 * @param schedulingInterval the schedulingInterval to set
 	 */
-	protected void setSchedulingInterval(double schedulingInterval) {
+	protected void setSchedulingInterval(final double schedulingInterval) {
 		this.schedulingInterval = schedulingInterval;
 	}
 

modules/cloudsim/src/main/java/org/cloudbus/cloudsim/power/PowerVmSelectionPolicyMaximumCorrelation.java

@@ -11,9 +11,9 @@ package org.cloudbus.cloudsim.power;
 import java.util.LinkedList;
 import java.util.List;
 
+import org.apache.commons.math3.linear.Array2DRowRealMatrix;
 import org.cloudbus.cloudsim.Vm;
-
-import flanagan.analysis.Regression;
+import org.cloudbus.cloudsim.util.MathUtil;
 
 /**
  * The Maximum Correlation (MC) VM selection policy.
@@ -39,19 +39,19 @@ public class PowerVmSelectionPolicyMaximumCorrelation extends PowerVmSelectionPo
 	 * 
 	 * @param fallbackPolicy the fallback policy
 	 */
-	public PowerVmSelectionPolicyMaximumCorrelation(PowerVmSelectionPolicy fallbackPolicy) {
+	public PowerVmSelectionPolicyMaximumCorrelation(final PowerVmSelectionPolicy fallbackPolicy) {
 		super();
 		setFallbackPolicy(fallbackPolicy);
 	}
 
 	/*
 	 * (non-Javadoc)
-	 * @see
-	 * org.cloudbus.cloudsim.experiments.power.PowerVmSelectionPolicy#getVmsToMigrate(org.cloudbus
-	 * .cloudsim.power.PowerHost)
+	 * 
+	 * @see org.cloudbus.cloudsim.experiments.power.PowerVmSelectionPolicy#
+	 * getVmsToMigrate(org.cloudbus .cloudsim.power.PowerHost)
 	 */
 	@Override
-	public Vm getVmToMigrate(PowerHost host) {
+	public Vm getVmToMigrate(final PowerHost host) {
 		List<PowerVm> migratableVms = getMigratableVms(host);
 		if (migratableVms.isEmpty()) {
 			return null;
@@ -80,7 +80,7 @@ public class PowerVmSelectionPolicyMaximumCorrelation extends PowerVmSelectionPo
 	 * @param vmList the host
 	 * @return the utilization matrix
 	 */
-	protected double[][] getUtilizationMatrix(List<PowerVm> vmList) {
+	protected double[][] getUtilizationMatrix(final List<PowerVm> vmList) {
 		int n = vmList.size();
 		int m = getMinUtilizationHistorySize(vmList);
 		double[][] utilization = new double[n][m];
@@ -99,7 +99,7 @@ public class PowerVmSelectionPolicyMaximumCorrelation extends PowerVmSelectionPo
 	 * @param vmList the vm list
 	 * @return the min utilization history size
 	 */
-	protected int getMinUtilizationHistorySize(List<PowerVm> vmList) {
+	protected int getMinUtilizationHistorySize(final List<PowerVm> vmList) {
 		int minSize = Integer.MAX_VALUE;
 		for (PowerVm vm : vmList) {
 			int size = vm.getUtilizationHistory().size();
@@ -116,7 +116,7 @@ public class PowerVmSelectionPolicyMaximumCorrelation extends PowerVmSelectionPo
 	 * @param data the data
 	 * @return the correlation coefficients
 	 */
-	protected List<Double> getCorrelationCoefficients(double[][] data) {
+	protected List<Double> getCorrelationCoefficients(final double[][] data) {
 		int n = data.length;
 		int m = data[0].length;
 		List<Double> correlationCoefficients = new LinkedList<Double>();
@@ -129,9 +129,12 @@ public class PowerVmSelectionPolicyMaximumCorrelation extends PowerVmSelectionPo
 				}
 			}
 
-			Regression reg = new Regression(x, data[i]);
-			reg.linear();
-			correlationCoefficients.add(reg.getCoefficientOfDetermination());
+			// Transpose the matrix so that it fits the linear model
+			double[][] xT = new Array2DRowRealMatrix(x).transpose().getData();
+
+			// RSquare is the "coefficient of determination"
+			correlationCoefficients.add(MathUtil.createLinearRegression(xT,
+					data[i]).calculateRSquared());
 		}
 		return correlationCoefficients;
 	}
@@ -150,7 +153,7 @@ public class PowerVmSelectionPolicyMaximumCorrelation extends PowerVmSelectionPo
 	 * 
 	 * @param fallbackPolicy the new fallback policy
 	 */
-	public void setFallbackPolicy(PowerVmSelectionPolicy fallbackPolicy) {
+	public void setFallbackPolicy(final PowerVmSelectionPolicy fallbackPolicy) {
 		this.fallbackPolicy = fallbackPolicy;
 	}
 

modules/cloudsim/src/main/java/org/cloudbus/cloudsim/util/MathUtil.java

@@ -11,14 +11,12 @@ package org.cloudbus.cloudsim.util;
 import java.util.Arrays;
 import java.util.List;
 
-import flanagan.analysis.Regression;
-import flanagan.analysis.Stat;
+import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics;
+import org.apache.commons.math3.stat.regression.OLSMultipleLinearRegression;
+import org.apache.commons.math3.stat.regression.SimpleRegression;
 
 /**
- * A class containing multiple convenient math functions. To use some of the function you must
- * download Michael Thomas Flanagan's Java Scientific Library:
- * 
- * http://www.ee.ucl.ac.uk/~mflanaga/java/
+ * A class containing multiple convenient math functions.
  * 
  * @author Anton Beloglazov
  * @since CloudSim Toolkit 3.0
@@ -31,7 +29,7 @@ public class MathUtil {
 	 * @param list the list
 	 * @return the double
 	 */
-	public static double sum(List<? extends Number> list) {
+	public static double sum(final List<? extends Number> list) {
 		double sum = 0;
 		for (Number number : list) {
 			sum += number.doubleValue();
@@ -45,7 +43,7 @@ public class MathUtil {
 	 * @param list the list
 	 * @return the double[]
 	 */
-	public static double[] listToArray(List<? extends Number> list) {
+	public static double[] listToArray(final List<? extends Number> list) {
 		double[] array = new double[list.size()];
 		for (int i = 0; i < array.length; i++) {
 			array[i] = list.get(i).doubleValue();
@@ -59,8 +57,54 @@ public class MathUtil {
 	 * @param list the list
 	 * @return the median
 	 */
-	public static double median(List<Double> list) {
-		return Stat.median(listToArray(list));
+	public static double median(final List<Double> list) {
+		return getStatistics(list).getPercentile(50);
+	}
+
+	/**
+	 * Gets the median.
+	 * 
+	 * @param list the list
+	 * 
+	 * @return the median
+	 */
+	public static double median(final double[] list) {
+		return getStatistics(list).getPercentile(50);
+	}
+
+	/**
+	 * Returns descriptive statistics for the list of numbers.
+	 * 
+	 * @param list
+	 *            - the list of numbers. Must not be null.
+	 * @return - descriptive statistics for the list of numbers.
+	 */
+	public static DescriptiveStatistics getStatistics(final List<Double> list) {
+		// Get a DescriptiveStatistics instance
+		DescriptiveStatistics stats = new DescriptiveStatistics();
+
+		// Add the data from the array
+		for (Double d : list) {
+			stats.addValue(d);
+		}
+		return stats;
+	}
+
+	/**
+	 * Returns descriptive statistics for the array of numbers.
+	 * 
+	 * @param list - the array of numbers. Must not be null.
+	 * @return - descriptive statistics for the array of numbers.
+	 */
+	public static DescriptiveStatistics getStatistics(final double[] list) {
+		// Get a DescriptiveStatistics instance
+		DescriptiveStatistics stats = new DescriptiveStatistics();
+
+		// Add the data from the array
+		for (int i = 0; i < list.length; i++) {
+			stats.addValue(list[i]);
+		}
+		return stats;
 	}
 
 	/**
@@ -70,7 +114,7 @@ public class MathUtil {
 	 * 
 	 * @return the average
 	 */
-	public static double mean(List<Double> list) {
+	public static double mean(final List<Double> list) {
 		double sum = 0;
 		for (Double number : list) {
 			sum += number;
@@ -84,7 +128,7 @@ public class MathUtil {
 	 * @param list the list
 	 * @return the double
 	 */
-	public static double variance(List<Double> list) {
+	public static double variance(final List<Double> list) {
 		long n = 0;
 		double mean = mean(list);
 		double s = 0.0;
@@ -106,7 +150,7 @@ public class MathUtil {
 	 * @param list the list
 	 * @return the double
 	 */
-	public static double stDev(List<Double> list) {
+	public static double stDev(final List<Double> list) {
 		return Math.sqrt(variance(list));
 	}
 
@@ -116,15 +160,15 @@ public class MathUtil {
 	 * @param data the data
 	 * @return the mad
 	 */
-	public static double mad(double[] data) {
+	public static double mad(final double[] data) {
 		double mad = 0;
 		if (data.length > 0) {
-			double median = Stat.median(data);
+			double median = median(data);
 			double[] deviationSum = new double[data.length];
 			for (int i = 0; i < data.length; i++) {
 				deviationSum[i] = Math.abs(median - data[i]);
 			}
-			mad = Stat.median(deviationSum);
+			mad = median(deviationSum);
 		}
 		return mad;
 	}
@@ -135,7 +179,7 @@ public class MathUtil {
 	 * @param data the data
 	 * @return the IQR
 	 */
-	public static double iqr(double[] data) {
+	public static double iqr(final double[] data) {
 		Arrays.sort(data);
 		int q1 = (int) Math.round(0.25 * (data.length + 1)) - 1;
 		int q3 = (int) Math.round(0.75 * (data.length + 1)) - 1;
@@ -148,7 +192,7 @@ public class MathUtil {
 	 * @param data the data
 	 * @return the int
 	 */
-	public static int countNonZeroBeginning(double[] data) {
+	public static int countNonZeroBeginning(final double[] data) {
 		int i = data.length - 1;
 		while (i >= 0) {
 			if (data[i--] != 0) {
@@ -164,7 +208,7 @@ public class MathUtil {
 	 * @param data the data
 	 * @return the int
 	 */
-	public static int countShortestRow(double[][] data) {
+	public static int countShortestRow(final double[][] data) {
 		int minLength = 0;
 		for (double[] row : data) {
 			if (row.length < minLength) {
@@ -180,7 +224,7 @@ public class MathUtil {
 	 * @param data the data
 	 * @return the double[]
 	 */
-	public static double[] trimZeroTail(double[] data) {
+	public static double[] trimZeroTail(final double[] data) {
 		return Arrays.copyOfRange(data, 0, countNonZeroBeginning(data));
 	}
 
@@ -190,19 +234,58 @@ public class MathUtil {
 	 * @param y the y
 	 * @return the loess parameter estimates
 	 */
-	public static double[] getLoessParameterEstimates(double[] y) {
+	public static double[] getLoessParameterEstimates(final double[] y) {
 		int n = y.length;
 		double[] x = new double[n];
 		for (int i = 0; i < n; i++) {
 			x[i] = i + 1;
 		}
-		Regression regression = new Regression(x, y, getTricubeWeigts(n));
-		regression.linear();
-		double[] estimates = regression.getBestEstimates();
-		if (estimates[0] == Double.NaN || estimates[1] == Double.NaN) {
-			return regression.getBestEstimates();
+		return createWeigthedLinearRegression(x, y, getTricubeWeigts(n))
+				.regress().getParameterEstimates();
+	}
+
+	public static SimpleRegression createLinearRegression(final double[] x,
+			final double[] y) {
+		SimpleRegression regression = new SimpleRegression();
+		for (int i = 0; i < x.length; i++) {
+			regression.addData(x[i], y[i]);
 		}
-		return estimates;
+		return regression;
+	}
+
+	public static OLSMultipleLinearRegression createLinearRegression(
+			final double[][] x, final double[] y) {
+		OLSMultipleLinearRegression regression = new OLSMultipleLinearRegression();
+		regression.newSampleData(y, x);
+		return regression;
+	}
+
+	public static SimpleRegression createWeigthedLinearRegression(
+			final double[] x, final double[] y, final double[] weigths) {
+		double[] xW = new double[x.length];
+		double[] yW = new double[y.length];
+
+		// As to Flanagan's documentation they perform weigthed regression if the
+		// number or non-zero weigths is more than 40%
+		int numZeroWeigths = 0;
+		for (int i = 0; i < weigths.length; i++) {
+			if (weigths[i] <= 0) {
+				numZeroWeigths++;
+			}
+		}
+
+		for (int i = 0; i < x.length; i++) {
+			if (numZeroWeigths >= 0.4 * weigths.length) {
+				// See: http://www.ncsu.edu/crsc/events/ugw07/Presentations/Crooks_Qiao/Crooks_Qiao_Alt_Presentation.pdf
+				xW[i] = Math.sqrt(weigths[i]) * x[i];
+				yW[i] = Math.sqrt(weigths[i]) * y[i];
+			} else {
+				xW[i] = x[i];
+				yW[i] = y[i];
+			}
+		}
+
+		return createLinearRegression(xW, yW);
 	}
 
 	/**
@@ -211,19 +294,25 @@ public class MathUtil {
 	 * @param y the y
 	 * @return the robust loess parameter estimates
 	 */
-	public static double[] getRobustLoessParameterEstimates(double[] y) {
+	public static double[] getRobustLoessParameterEstimates(final double[] y) {
 		int n = y.length;
 		double[] x = new double[n];
 		for (int i = 0; i < n; i++) {
 			x[i] = i + 1;
 		}
-		Regression regression = new Regression(x, y, getTricubeWeigts(n));
-		regression.linear();
-		Regression regression2 = new Regression(x, y, getTricubeBisquareWeigts(regression.getResiduals()));
-		regression2.linear();
-		double[] estimates = regression2.getBestEstimates();
+		SimpleRegression tricubeRegression = createWeigthedLinearRegression(x,
+				y, getTricubeWeigts(n));
+		double[] residuals = new double[n];
+		for (int i = 0; i < n; i++) {
+			residuals[i] = y[i] - tricubeRegression.predict(x[i]);
+		}
+		SimpleRegression tricubeBySquareRegression = createWeigthedLinearRegression(
+				x, y, getTricubeBisquareWeigts(residuals));
+
+		double[] estimates = tricubeBySquareRegression.regress()
+				.getParameterEstimates();
 		if (estimates[0] == Double.NaN || estimates[1] == Double.NaN) {
-			return regression.getBestEstimates();
+			return tricubeRegression.regress().getParameterEstimates();
 		}
 		return estimates;
 	}
@@ -234,7 +323,7 @@ public class MathUtil {
 	 * @param n the n
 	 * @return the tricube weigts
 	 */
-	public static double[] getTricubeWeigts(int n) {
+	public static double[] getTricubeWeigts(final int n) {
 		double[] weights = new double[n];
 		double top = n - 1;
 		double spread = top;
@@ -256,11 +345,11 @@ public class MathUtil {
 	 * @param residuals the residuals
 	 * @return the tricube bisquare weigts
 	 */
-	public static double[] getTricubeBisquareWeigts(double[] residuals) {
+	public static double[] getTricubeBisquareWeigts(final double[] residuals) {
 		int n = residuals.length;
 		double[] weights = getTricubeWeigts(n);
 		double[] weights2 = new double[n];
-		double s6 = Stat.median(abs(residuals)) * 6;
+		double s6 = median(abs(residuals)) * 6;
 		for (int i = 2; i < n; i++) {
 			double k = Math.pow(1 - Math.pow(residuals[i] / s6, 2), 2);
 			if (k > 0) {
@@ -279,7 +368,7 @@ public class MathUtil {
 	 * @param data the data
 	 * @return the double[]
 	 */
-	public static double[] abs(double[] data) {
+	public static double[] abs(final double[] data) {
 		double[] result = new double[data.length];
 		for (int i = 0; i < result.length; i++) {
 			result[i] = Math.abs(data[i]);

modules/pom.xml

@@ -17,6 +17,16 @@
 
   <build>
     <plugins>
+      <!-- Sets the version of the code -->
+      <plugin>
+      	<groupId>org.apache.maven.plugins</groupId>
+      		<artifactId>maven-compiler-plugin</artifactId>
+      		<configuration>
+      		<source>1.6</source>
+      		<target>1.6</target>
+      		</configuration>
+      </plugin>
+
       <plugin>
         <inherited>true</inherited>
         <groupId>org.apache.maven.plugins</groupId>
@@ -49,10 +59,11 @@
     <artifactId>easymockclassextension</artifactId>
   </dependency>
   <dependency>
-    <groupId>org.flanagan</groupId>
-    <artifactId>flanagan</artifactId>
-    <version>1.0</version>
-  </dependency>                
+    <groupId>org.apache.commons</groupId>
+    <artifactId>commons-math3</artifactId>
+    <version>3.0</version>
+  </dependency>
+              
   </dependencies>
   
-</project>
+</project>
\ No newline at end of file