Package jline.lang.processes

Class Det

java.lang.Object
jline.lang.processes.Distribution
jline.lang.processes.Det
All Implemented Interfaces:
Serializable, Copyable
public class Det extends Distribution implements Serializable
A Deterministic distribution taking a single constant value.
See Also:

  • Field Details

  • Constructor Details

    • Det

      public Det(double t)
      Creates a deterministic distribution with the specified constant value.
      Parameters:
      t - the constant value for this deterministic distribution

  • Method Details

    • fitMean

      public static Det fitMean(double mean)
      Creates a deterministic distribution with the specified mean value. This is equivalent to new Det(mean).
      Parameters:
      mean - the mean value for the deterministic distribution
      Returns:
      a new Det distribution with the specified mean

    • evalCDF

      public double evalCDF(double t)
      Evaluates the cumulative distribution function at the given point. Returns 0 if t < value, 1 if t >= value.
      Specified by:
      evalCDF in class Distribution
      Parameters:
      t - the point at which to evaluate the CDF
      Returns:
      0 or 1 depending on whether t has reached the deterministic value

    • evalLST

      public double evalLST(double s)
      Evaluates the Laplace-Stieltjes transform at the given point.
      Specified by:
      evalLST in class Distribution
      Parameters:
      s - the transform variable
      Returns:
      e^(-s*t) where t is the deterministic value

    • evalLST

      public org.apache.commons.math3.complex.Complex evalLST(org.apache.commons.math3.complex.Complex s)
      The transform at a COMPLEX argument, exp(-s d), exact and analytic. The CDF sum of Distribution.evalLST(org.apache.commons.math3.complex.Complex) cannot see this law at all: its measure is a single atom, which no grid of increments resolves.
      Overrides:
      evalLST in class Distribution
      Parameters:
      s - the Laplace domain variable
      Returns:
      the LST value at s

    • getMean

      public double getMean()
      Gets the mean of this deterministic distribution.
      Specified by:
      getMean in class Distribution
      Returns:
      the constant value of the distribution

    • setMean

      public void setMean(double t)
      Sets the mean (constant value) of this deterministic distribution.
      Parameters:
      t - the new constant value

    • getMu

      public double getMu()
      Gets the rate (inverse of the constant value).
      Returns:
      1/t where t is the deterministic value

    • getPhi

      public double getPhi()
      Gets the phase parameter.
      Returns:
      always returns 1 for deterministic distribution

    • getRepresentation

      public MatrixCell getRepresentation()
      Gets the process representation with actual distribution parameters. Returns MatrixCell{[t]} for deterministic value.
      Returns:
      MatrixCell containing the distribution parameter

    • getProcess

      public Map<Integer,Matrix> getProcess()
      Gets the matrix representation of this deterministic process (for PH compatibility).
      Returns:
      map containing the process matrices

    • setProcess

      public void setProcess(Map<Integer,Matrix> proc)
      Sets the matrix representation of this deterministic process.
      Parameters:
      proc - the process matrices to set

    • getRate

      public double getRate()
      Gets the rate of this deterministic distribution.
      Overrides:
      getRate in class Distribution
      Returns:
      1/t where t is the deterministic value

    • getSCV

      public double getSCV()
      Gets the squared coefficient of variation. For deterministic distribution, SCV = 0 (no variance).
      Specified by:
      getSCV in class Distribution
      Returns:
      always returns 0

    • getSkewness

      public double getSkewness()
      Gets the skewness of this deterministic distribution.
      Specified by:
      getSkewness in class Distribution
      Returns:
      always returns 0 (no skewness)

    • getVar

      public double getVar()
      Gets the variance of this deterministic distribution.
      Overrides:
      getVar in class Distribution
      Returns:
      always returns 0 (no variance)

    • isContinuous

      public boolean isContinuous()
      Description copied from class: Distribution
      Checks if this is a continuous distribution.
      Overrides:
      isContinuous in class Distribution
      Returns:
      true if this is a continuous distribution, false otherwise

    • isDisabled

      public boolean isDisabled()
      Description copied from class: Distribution
      Checks if this is a disabled distribution.
      Overrides:
      isDisabled in class Distribution
      Returns:
      true if this is a disabled distribution, false otherwise

    • isDiscrete

      public boolean isDiscrete()
      Description copied from class: Distribution
      Checks if this is a discrete distribution.
      Overrides:
      isDiscrete in class Distribution
      Returns:
      true if this is a discrete distribution, false otherwise

    • isImmediate

      public boolean isImmediate()
      Description copied from class: Distribution
      Checks if this distribution has immediate (zero) service time.
      Overrides:
      isImmediate in class Distribution
      Returns:
      true if the distribution is immediate or has mean < Zero threshold

    • sample

      public double[] sample(int n)
      Description copied from class: Distribution
      Generates random samples from this distribution using default random generator.
      Overrides:
      sample in class Distribution
      Parameters:
      n - the number of samples to generate
      Returns:
      array of random samples

    • sample

      public double[] sample(int n, Random random)
      Description copied from class: Distribution
      Generates random samples from this distribution using the specified random generator.
      Specified by:
      sample in class Distribution
      Parameters:
      n - the number of samples to generate
      random - the random number generator to use
      Returns:
      array of random samples

    • mu

      public double mu()
      Property alias for getMu

    • phi

      public double phi()
      Property alias for getPhi

    • process

      public Map<Integer,Matrix> process()
      Property alias for getProcess

    • mean

      public double mean()
      Property alias for getMean
      Overrides:
      mean in class Distribution

    • rate

      public double rate()
      Property alias for getRate
      Overrides:
      rate in class Distribution

    • scv

      public double scv()
      Property alias for getSCV
      Overrides:
      scv in class Distribution

    • skewness

      public double skewness()
      Property alias for getSkewness
      Overrides:
      skewness in class Distribution

    • var

      public double var()
      Property alias for getVar
      Overrides:
      var in class Distribution