Package jline.lib.kpctoolbox.mmpp

Class MMPPKt

  • All Implemented Interfaces:
    
public final class MMPPKt

    • Constructor Detail

    • Method Detail

      • mmpp2_fit3

         final static MatrixCell mmpp2_fit3(Double E1, Double E2, Double E3, Double G2)

        Fits a 2-state MMPP to match first three moments and G2 parameter.

        This is the core MMPP2 fitter matching MATLAB's mmpp2_fit3(E1,E2,E3,G2). G2 specifies the ratio of consecutive autocorrelations: rho(i)/rho(i-1).

        Parameters:
        E1 - First moment (mean)
        E2 - Second moment
        E3 - Third moment
        G2 - Autocorrelation decay ratio
        Returns:

        Fitted MAP as {D0, D1}

      • mmpp2_fit1

         final static MatrixCell mmpp2_fit1(Double mean, Double scv, Double skew, Double idc)

        Fits MMPP2 from mean, SCV, skewness, and index of dispersion for counts.

        Matches MATLAB: mmpp2_fit1(mean, scv, skew, idc)

        Parameters:
        mean - Mean inter-arrival time
        scv - Squared coefficient of variation
        skew - Skewness (-1 for automatic)
        idc - Index of dispersion for counts
        Returns:

        Fitted MAP as {D0, D1}

      • mmpp2_fit2

         final static MatrixCell mmpp2_fit2(Double mean, Double scv, Double skew, Double g2)

        Fits MMPP2 from mean, SCV, skewness, and G2 parameter.

        Matches MATLAB: mmpp2_fit2(mean, scv, skew, g2)

        Parameters:
        mean - Mean inter-arrival time
        scv - Squared coefficient of variation
        skew - Skewness
        g2 - Autocorrelation decay ratio
        Returns:

        Fitted MAP as {D0, D1}

      • mmpp2_fit4

         final static MatrixCell mmpp2_fit4(Double mean, Double scv, Double skew, Double acf1)

        Fits MMPP2 from mean, SCV, skewness, and lag-1 autocorrelation.

        Matches MATLAB: mmpp2_fit4(mean, scv, skew, acf1)

        Parameters:
        mean - Mean inter-arrival time
        scv - Squared coefficient of variation
        skew - Skewness (-1 for automatic)
        acf1 - Lag-1 autocorrelation
        Returns:

        Fitted MAP as {D0, D1}

      • mmpp2_fitc

         final static MatrixCell mmpp2_fitc(Double mu, Double bt1, Double bt2, Double binf, Double m3t2, Double t1, Double t2)

        Fits MMPP2 from counting process statistics using Heffes-Lucantoni method.

        Matches MATLAB: mmpp2_fitc(mu, bt1, bt2, binf, m3t2, t1, t2)

        Parameters:
        mu - Arrival rate
        bt1 - IDC at scale t1
        bt2 - IDC at scale t2
        binf - IDC for t->inf
        m3t2 - Third central moment at scale t2
        t1 - First time scale
        t2 - Second time scale
        Returns:

        Fitted MAP as {D0, D1}

      • mmpp2_fitc_approx

         final static MatrixCell mmpp2_fitc_approx(Double a, Double bt1, Double bt2, Double binf, Double m3t2, Double t1, Double t2)

        Fits MMPP2 from counting process statistics using optimization.

        Matches MATLAB: mmpp2_fitc_approx(a, bt1, bt2, binf, m3t2, t1, t2)

        Parameters:
        a - Arrival rate
        bt1 - IDC at scale t1
        bt2 - IDC at scale t2
        binf - IDC for t->inf
        m3t2 - Third central moment at scale t2
        t1 - First time scale
        t2 - Second time scale
        Returns:

        Fitted MAP as {D0, D1}

      • mmpp2_fitc_theoretical

         final static MatrixCell mmpp2_fitc_theoretical(MatrixCell MAP, Double t1, Double t2, Double tinf)

        Fits theoretical characteristics of a MAP(n) with a MMPP(2).

        Matches MATLAB: mmpp2_fitc_theoretical(map, t1, t2, tinf)

        Parameters:
        MAP - Input MAP as {D0, D1, ...
        t1 - First time scale (default 1)
        t2 - Second time scale (default 10)
        tinf - Large time scale for asymptotic IDC (default 1e8)
        Returns:

        Fitted MMPP2 as {D0, D1}

      • mmpp_rand

         final static MatrixCell mmpp_rand(Integer K)

        Generates a random MMPP with K states.

        Matches MATLAB: mmpp_rand(K) - generates random D0, D1 (diagonal), normalizes.

        Parameters:
        K - Number of states
        Returns:

        Random MMPP as {D0, D1}

      • mmpp_rand

         final static MatrixCell mmpp_rand()

        Generates a random MMPP with 2 states.

        Returns:

        Random MMPP as {D0, D1}