Example usage for org.apache.commons.math3.analysis MultivariateFunction interface-usage

Introduction

In this page you can find the example usage for org.apache.commons.math3.analysis MultivariateFunction interface-usage.

Usage

From source file nl.systemsgenetics.cellTypeSpecificAlleleSpecificExpression.Function.java

/**
 *
 * @author adriaan
 */
public interface Function extends MultivariateFunction {

From source file com.insightml.math.optimization.Optimizable.java

public interface Optimizable extends MultivariateFunction {

    Triple<double[], Double, Double> max(MultivariateFunction test, double[] initial);

}

From source file edu.utexas.cs.tactex.tariffoptimization.OptimizerWrapperApacheObjective.java

public class OptimizerWrapperApacheObjective implements MultivariateFunction {

    private TariffUtilityEstimate tariffUtilityEstimate;

    public OptimizerWrapperApacheObjective(TariffUtilityEstimate tariffUtilityEstimate) {
        this.tariffUtilityEstimate = tariffUtilityEstimate;

From source file com.itemanalysis.psychometrics.analysis.AbstractMultivariateFunction.java

/**
 * Abstract class that includes methods for numeric computations of teh gradientAt, partial derivatives, and hessian.
 * Extend this class with an implementation of the rho(double[] x) method as specified in the MultivariateRealFunction
 * interface.
 *
 */

From source file de.bund.bfr.math.LodFunction.java

public class LodFunction implements MultivariateFunction {

    private List<String> parameters;
    private Map<String, List<Double>> variableValues;
    private List<Double> targetValues;
    private double levelOfDetection;

From source file edu.ucsf.valelab.saim.calculations.SaimErrorFunction.java

/**
 * Calculates the error (as sum of absolute errors) between given set of 
 * data points and theoretical prediction given A, B, and h).
 * 
 * @author nico
 */

From source file objenome.goal.numeric.OptimizeMultivariate.java

/**
 * Multivariate Optmization with Multistart which uses different starting points 
 * (trying to avoid being trapped in a local extremum when looking for a global one)
 * @see http://commons.apache.org/proper/commons-math/javadocs/api-3.3/src-html/org/apache/commons/math3/optim/nonlinear/scalar/MultiStartMultivariateOptimizer.html
 */
public class OptimizeMultivariate<C> extends NumericSolver<C> implements MultivariateFunction {

From source file org.compevol.ssgd.LogLikelihoodFunction.java

/**
 * @author Arman Bilge <armanbilge@gmail.com>
 */
public class LogLikelihoodFunction implements MultivariateFunction {

    private final Likelihood function;

From source file norbert.mynemo.core.selection.SvdRecommenderEvalFunction.java

/**
 * This function renders optimizable the numbers of features and iterations for a SVD based
 * recommender. Indeed, the {@link #value(double[])} method takes the two numbers as parameter, and
 * returns the value of a metric produced by an evaluator for these numbers. A list of all
 * evaluations performed are kept, and can be accessed via the {@link #getEvaluations()} method.
 *

From source file norbert.mynemo.core.selection.UserBasedRecommenderEvaluationFunction.java

/**
 * This function renders optimizable the number of neighbors for a user-similarity based
 * recommender. Indeed, the {@link #value(double)} method takes a number of neighbors as parameter,
 * and returns the value of a metric produced by an evaluator for that number of neighbors. A list
 * of all evaluations performed are kept, and can be accessed via the {@link #getEvaluations()}
 * method.

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