Package jline.lang.processes

Class Prior

  • All Implemented Interfaces:
    java.io.Serializable , jline.lang.Copyable 
    
public class Prior
extends Distribution implements Serializable

    Prior distribution representing parameter uncertainty over alternative distributions. Prior represents parameter uncertainty by specifying a discrete set of alternative distributions with associated probabilities. When used with setService or setArrival, it causes the Posterior solver to expand the model into a family of networks, one for each alternative. This is NOT a mixture distribution - each alternative represents a separate model realization with its associated prior probability. Example usage: 

    List<Distribution> dists = Arrays.asList(new Exp(1.0), new Exp(2.0), new Erlang(1.5, 2));
double[] probs = {0.4, 0.35, 0.25};
Prior prior = new Prior(dists, probs);
queue.setService(jobclass, prior);

    • Nested Class Summary

      Nested Classes 
      Modifier and Type Class Description

    • Constructor Summary

      Constructors 
      Constructor Description
      Prior(List<Distribution> distributions, Array<double> probabilities) Creates a Prior distribution with specified alternatives and probabilities.
      Prior(Array<Distribution> distributions, Array<double> probabilities) Convenience constructor for array-based input.

    • Enum Constant Summary

      Enum Constants 
      Enum Constant Description

    • Method Summary

      Modifier and Type Method Description
      int getNumAlternatives() Returns the number of alternative distributions.
      Distribution getAlternative(int idx) Returns the distribution at the specified index.
      double getProbability(int idx) Returns the probability of the alternative at the specified index.
      Array<double> getProbabilities() Returns the array of all probabilities.
      List<Distribution> getDistributions() Returns the list of all distributions.
      double getMean() Gets the prior-weighted mean (expected mean over alternatives).
      double getSCV() Gets the prior-weighted SCV using law of total variance.
      double getSkewness() Gets the prior-weighted skewness.
      Array<double> sample(int n, Random random) Generates random samples from the Prior (mixture sampling).
      double evalCDF(double t) Evaluates the mixture CDF at t.
      double evalLST(double s) Evaluates the mixture Laplace-Stieltjes transform.
      boolean isPrior() Returns true indicating this is a Prior distribution.
      static boolean isPriorDistribution(Distribution dist) Static method to check if a distribution is a Prior.

      • Methods inherited from class jline.lang.processes.Distribution

        evalProbInterval, getName, getNumParams, getParam, getRate, getSupport, getVar, isContinuous, isDisabled, isDiscrete, isImmediate, isMarkovian, mean, name, numParams, param, rate, sample, scv, setNumParams, setParam, skewness, support, var

      • Methods inherited from class jline.lang.Copyable

        copy

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Constructor Detail

      • Prior

        Prior(List<Distribution> distributions, Array<double> probabilities)
        Creates a Prior distribution with specified alternatives and probabilities.
        Parameters:
        distributions - list of alternative Distribution objects
        probabilities - array of probabilities (must sum to 1 and be non-negative)

      • Prior

        Prior(Array<Distribution> distributions, Array<double> probabilities)
        Convenience constructor for array-based input.
        Parameters:
        distributions - array of alternative Distribution objects
        probabilities - array of probabilities

    • Method Detail

      • getNumAlternatives

         int getNumAlternatives()

        Returns the number of alternative distributions.

        Returns:

        number of alternatives

      • getAlternative

         Distribution getAlternative(int idx)

        Returns the distribution at the specified index.

        Parameters:
        idx - 0-based index
        Returns:

        the distribution at index idx

      • getProbability

         double getProbability(int idx)

        Returns the probability of the alternative at the specified index.

        Parameters:
        idx - 0-based index
        Returns:

        the probability at index idx

      • getProbabilities

         Array<double> getProbabilities()

        Returns the array of all probabilities.

        Returns:

        copy of probability array

      • getMean

         double getMean()

        Gets the prior-weighted mean (expected mean over alternatives). E[X] = sum_i p_i * E[X_i]

        Returns:

        the weighted mean

      • getSCV

         double getSCV()

        Gets the prior-weighted SCV using law of total variance. Var(X) = E[Var(X|D)] + Var(E[X|D]) SCV = Var(X) / E[X]^2

        Returns:

        the weighted SCV

      • getSkewness

         double getSkewness()

        Gets the prior-weighted skewness. Uses mixture formula with moment calculations.

        Returns:

        the weighted skewness

      • sample

         Array<double> sample(int n, Random random)

        Generates random samples from the Prior (mixture sampling). Each sample is drawn from one of the alternatives selected according to the prior probabilities.

        Parameters:
        n - number of samples
        random - the random number generator
        Returns:

        array of samples

      • evalCDF

         double evalCDF(double t)

        Evaluates the mixture CDF at t. F(t) = sum_i p_i * F_i(t)

        Parameters:
        t - the point at which to evaluate
        Returns:

        the CDF value

      • evalLST

         double evalLST(double s)

        Evaluates the mixture Laplace-Stieltjes transform. L(s) = sum_i p_i * L_i(s)

        Parameters:
        s - the transform variable
        Returns:

        the LST value

      • isPrior

         boolean isPrior()

        Returns true indicating this is a Prior distribution. Used for detection by Posterior solver.

        Returns:

        true

      • isPriorDistribution

         static boolean isPriorDistribution(Distribution dist)

        Static method to check if a distribution is a Prior.

        Parameters:
        dist - the distribution to check
        Returns:

        true if dist is a Prior