Package jline.solvers.des.handlers

Class Solver_ssjKt

  • All Implemented Interfaces:
    
public final class Solver_ssjKt

    • Constructor Detail

    • Method Detail

      • solver_ssj

         final static DESResult solver_ssj(NetworkStruct sn, SolverOptions options, Collector stream)
        Parameters:
        sn - Network structure representing the queueing network model
        options - Solver configuration options (samples = max events, seed, verbose, etc.
        Returns:

        DESResult with steady-state performance metrics

      • solver_ssj_transient

         final static DESResult solver_ssj_transient(NetworkStruct sn, SolverOptions options, Collector stream)
        Parameters:
        sn - Network structure representing the queueing network model
        options - Solver configuration options (timespan defines the analysis interval)
        Returns:

        DESResult with transient time-series metrics in QNt, UNt, TNt arrays

      • computeOBMStatistics

         final static Triple<Double, Double, Integer> computeOBMStatistics(List<Double> observations, Integer batchSize)

        Compute OBM (Overlapping Batch Means) statistics with 50% overlap. Exposed as top-level function for testing.

        Parameters:
        observations - List of observations to analyze
        batchSize - Size of each batch
        Returns:

        Triple(grandMean, stdError, effectiveDf) or null if insufficient data

      • getTCriticalValue

         final static Double getTCriticalValue(Double confintLevel, Integer df)

        Get t-distribution critical value for given confidence level and degrees of freedom. Exposed as top-level function for testing.

        Parameters:
        confintLevel - Confidence level (e.g., 0.
        df - Degrees of freedom
        Returns:

        Critical value from t-distribution

      • computeStandardBatchMeansStatistics

         final static Triple<Double, Double, Integer> computeStandardBatchMeansStatistics(List<Double> observations, Integer batchSize)

        Compute standard (non-overlapping) batch means statistics. Exposed as top-level function for testing comparison with OBM.

        Parameters:
        observations - List of observations to analyze
        batchSize - Size of each batch
        Returns:

        Triple(grandMean, stdError, effectiveDf) or null if insufficient data