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 Summary

    Fields
    Modifier and Type
    Field
    Description
    protected Map<Integer,Matrix>
    process
     

    Fields inherited from class jline.lang.processes.Distribution

    immediate, mean, name, numParam, params, support

  • Constructor Summary

    Constructors
    Constructor
    Description
    Det(double t)
    Creates a deterministic distribution with the specified constant value.

  • Method Summary

    Modifier and Type
    Method
    Description
    double
    evalCDF(double t)
    Evaluates the cumulative distribution function at the given point.
    double
    evalLST(double s)
    Evaluates the Laplace-Stieltjes transform at the given point.
    static Det
    fitMean(double mean)
    Creates a deterministic distribution with the specified mean value.
    double
    getMean()
    Gets the mean of this deterministic distribution.
    double
    getMu()
    Gets the rate (inverse of the constant value).
    double
    getPhi()
    Gets the phase parameter.
    Map<Integer,Matrix>
    getProcess()
    Gets the matrix representation of this deterministic process (for PH compatibility).
    double
    getRate()
    Gets the rate of this deterministic distribution.
    MatrixCell
    getRepresentation()
    Gets the process representation with actual distribution parameters.
    double
    getSCV()
    Gets the squared coefficient of variation.
    double
    getSkewness()
    Gets the skewness of this deterministic distribution.
    double
    getVar()
    Gets the variance of this deterministic distribution.
    boolean
    isContinuous()
    Checks if this is a continuous distribution.
    boolean
    isDisabled()
    Checks if this is a disabled distribution.
    boolean
    isDiscrete()
    Checks if this is a discrete distribution.
    boolean
    isImmediate()
    Checks if this distribution has immediate (zero) service time.
    double
    mean()
    Kotlin-style property alias for getMean()
    double
    mu()
    Kotlin-style property alias for getMu()
    double
    phi()
    Kotlin-style property alias for getPhi()
    Map<Integer,Matrix>
    process()
    Kotlin-style property alias for getProcess()
    double
    rate()
    Kotlin-style property alias for getRate()
    double[]
    sample(int n)
    Generates random samples from this distribution using default random generator.
    double[]
    sample(int n, Random random)
    Generates random samples from this distribution using the specified random generator.
    double
    scv()
    Kotlin-style property alias for getSCV()
    void
    setMean(double t)
    Sets the mean (constant value) of this deterministic distribution.
    void
    setProcess(Map<Integer,Matrix> proc)
    Sets the matrix representation of this deterministic process.
    double
    skewness()
    Kotlin-style property alias for getSkewness()
    double
    var()
    Kotlin-style property alias for getVar()

    Methods inherited from class jline.lang.processes.Distribution

    evalProbInterval, getName, getNumParams, getParam, getSupport, isMarkovian, name, numParams, param, setNumParams, setParam, support

    Methods inherited from class java.lang.Object

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

    Methods inherited from interface jline.lang.Copyable

    copy

  • 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 invalid input: '<' 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

    • 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 invalid input: '<' 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()
      Kotlin-style property alias for getMu()

    • phi

      public double phi()
      Kotlin-style property alias for getPhi()

    • process

      public Map<Integer,Matrix> process()
      Kotlin-style property alias for getProcess()

    • mean

      public double mean()
      Kotlin-style property alias for getMean()
      Overrides:
      mean in class Distribution

    • rate

      public double rate()
      Kotlin-style property alias for getRate()
      Overrides:
      rate in class Distribution

    • scv

      public double scv()
      Kotlin-style property alias for getSCV()
      Overrides:
      scv in class Distribution

    • skewness

      public double skewness()
      Kotlin-style property alias for getSkewness()
      Overrides:
      skewness in class Distribution

    • var

      public double var()
      Kotlin-style property alias for getVar()
      Overrides:
      var in class Distribution