/*
* JaamSim Discrete Event Simulation
* Copyright (C) 2013 Ausenco Engineering Canada Inc.
* Copyright (C) 2016 JaamSim Software Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.jaamsim.ProbabilityDistributions;
import com.jaamsim.Samples.SampleConstant;
import com.jaamsim.Samples.SampleInput;
import com.jaamsim.input.IntegerInput;
import com.jaamsim.input.Keyword;
import com.jaamsim.rng.MRG1999a;
import com.jaamsim.units.Unit;
import com.jaamsim.units.UserSpecifiedUnit;
/**
* Erlang Distribution.
* Adapted from A.M. Law, "Simulation Modelling and Analysis, 4th Edition", page 449.
*/
public class ErlangDistribution extends Distribution {
@Keyword(description = "The scale parameter for the Erlang distribution.",
exampleList = {"5.0", "InputValue1", "'2 * [InputValue1].Value'"})
private final SampleInput meanInput;
@Keyword(description = "The shape parameter for the Erlang distribution. An integer value >= 1. " +
"Shape = 1 gives the Exponential distribution. " +
"For Shape > 10 it is better to use the Gamma distribution.",
exampleList = {"2"})
private final IntegerInput shapeInput;
private final MRG1999a rng = new MRG1999a();
{
minValueInput.setDefaultValue(new SampleConstant(0.0d));
meanInput = new SampleInput("Mean", "Key Inputs", new SampleConstant(1.0d));
meanInput.setUnitType(UserSpecifiedUnit.class);
meanInput.setValidRange(0.0d, Double.POSITIVE_INFINITY);
meanInput.setEntity(this);
this.addInput(meanInput);
shapeInput = new IntegerInput("Shape", "Key Inputs", 1);
shapeInput.setValidRange( 1, Integer.MAX_VALUE);
this.addInput(shapeInput);
}
public ErlangDistribution() {}
@Override
public void earlyInit() {
super.earlyInit();
rng.setSeedStream(getStreamNumber(), getSubstreamNumber());
}
@Override
protected void setUnitType(Class<? extends Unit> specified) {
super.setUnitType(specified);
meanInput.setUnitType(specified);
}
@Override
protected double getSample(double simTime) {
// Calculate the product of k random values
double u = 1.0;
int k = shapeInput.getValue();
for( int i=0; i<k; i++) {
u *= rng.nextUniform();
}
// Inverse transform method
double mean = meanInput.getValue().getNextSample(simTime);
return (- mean / shapeInput.getValue() * Math.log( u ));
}
@Override
protected double getMean(double simTime) {
return meanInput.getValue().getNextSample(simTime);
}
@Override
protected double getStandardDev(double simTime) {
double mean = meanInput.getValue().getNextSample(simTime);
return mean / Math.sqrt( shapeInput.getValue() );
}
}