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Sensitivity Analysis of Model Output
There is a newer version: 0.0.3
package org.jamesii.samo.local;

import java.util.Map;
import org.jamesii.samo.IModel;

public class DifferentialImportance implements ILocalSensitivityAnalysis {
  private IModel model;
  private Map firstOrderDerivatives;
  private Map baseCase;
  private Map sensitivityCase;

  /**
   * The class DifferentialImportance implements local sensitivity analysis by using the first order
   * derivatives of the model as basis for a sensitivity measure.
   * 
   * 
   * See:
   * 

   * Borgonovo, Emanuele and Plischke, Elmar: "Sensitivity analysis: A review of recent
   * advances" (2016)
   * 
   * 
   * @param model model for sensitivity analysis
   * @param firstOrderDerivatives values of the first order derivatives of the model at the base
   *        case
   * @param baseCase point in parameter space
   * @param sensitivityCase point in parameter space
   */
  public DifferentialImportance(IModel model, Map firstOrderDerivatives,
      Map baseCase, Map sensitivityCase) {
    this.model = model;
    this.firstOrderDerivatives = firstOrderDerivatives;
    this.baseCase = baseCase;
    this.sensitivityCase = sensitivityCase;
  }

  /**
   * Calculates the elasticity of the specified parameter. The elasticity of a parameter denotes the
   * ratio of relative model change to relative input change.
   * 
   * @param parameter name of the model parameter
   * @return elasticity of the specified parameter
   */
  public double elasticity(String parameter) {
    double elasticity =
        firstOrderDerivatives.get(parameter) * (baseCase.get(parameter) / model.value(baseCase));
    return elasticity;
  }

  /**
   * Calculates the differential importance measure of the specified parameter. The differential
   * importance measure denotes ratio of differential change caused by the specified parameter to
   * the total differential change.
   * 
   * @param parameter name of the model parameter
   * @return differential importance measure of the specified parameter
   */
  public double differentialImportanceMeasure(String parameter) {
    double d = 0;
    double numerator = firstOrderDerivatives.get(parameter)
        * (sensitivityCase.get(parameter) - baseCase.get(parameter));
    double denominator = 0;
    for (String parameter2 : model.getParameters()) {
      denominator += firstOrderDerivatives.get(parameter2)
          * (sensitivityCase.get(parameter2) - baseCase.get(parameter2));
    }
    try {
      d = numerator / denominator;
    } catch (Exception e) {
      e.printStackTrace();
    }
    return d;
  }
}