Package jline.lang.processes

Class Distribution

java.lang.Object
jline.lang.processes.Distribution
All Implemented Interfaces:
Serializable, Copyable
Direct Known Subclasses:
ContinuousDistribution, Det, Disabled, DiscreteDistribution, EmpiricalCDF, Immediate, Prior, Replayer
public abstract class Distribution extends Object implements Copyable
An abstract class of a general distribution
See Also:

  • Field Summary

    Fields
    Modifier and Type
    Field
    Description
    protected boolean
    immediate
     
    protected double
    mean
     
    protected String
    name
     
    protected int
    numParam
     
    protected List<NamedParam>
    params
     
    protected Pair<Double,Double>
    support
     

  • Constructor Summary

    Constructors
    Constructor
    Description
    Distribution(String name, int numParam, Pair<Double,Double> support)
    Creates a new distribution with the specified characteristics.

  • Method Summary

    Modifier and Type
    Method
    Description
    abstract double
    evalCDF(double t)
    Evaluates the cumulative distribution function (CDF) at the given point.
    abstract double
    evalLST(double s)
    Evaluate the Laplace-Stieltjes Transform at s
    org.apache.commons.math3.complex.Complex
    evalLST(org.apache.commons.math3.complex.Complex s)
    Evaluate the Laplace-Stieltjes Transform at a COMPLEX argument.
    double
    evalProbInterval(double t0, double t1)
    Evaluates the probability of the distribution falling within the given interval.
    String
    getFeatureName()
    The registry name this distribution is marked under by Network.getUsedLangFeatures().
    abstract double
    getMean()
    Gets the mean (expected value) of this distribution.
    String
    getName()
    Gets the name of this distribution type.
    int
    getNumParams()
    Gets the number of parameters of this distribution, twin of the MATLAB getNumParams(), which reports length(params).
    int
    getNumParams(int id)
    Gets the number of parameters for this distribution.
    NamedParam
    getParam(int id)
    Gets a parameter by its ID.
    NamedParam
    getParam(String name)
    Returns the parameter carrying a given name, twin of reading the MATLAB params cell by its paramName field.
    List<NamedParam>
    getParams()
    Returns every parameter of this distribution, in declaration order.
    double
    getRate()
    Gets the rate of this distribution (inverse of mean).
    abstract double
    getSCV()
    Gets the squared coefficient of variation (SCV) of this distribution.
    abstract double
    getSkewness()
    Gets the skewness of this distribution.
    Pair<Double,Double>
    getSupport()
    Gets the support range of this distribution.
    double
    getVar()
    Gets the variance of this distribution.
    boolean
    hasParam(int id)
    Tests whether a parameter has been set at the given position, i.e.
    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.
    boolean
    isMarkovian()
    Check if this distribution is Markovian (has a matrix process representation)
    double
    mean()
    Property alias for getMean
    String
    name()
    Property alias for getName
    int
    numParams(int id)
    Property alias for getNumParams(int id)
    NamedParam
    param(int id)
    Property alias for getParam(int id)
    double
    rate()
    Property alias for getRate
    double[]
    sample(int n)
    Generates random samples from this distribution using default random generator.
    abstract double[]
    sample(int n, Random random)
    Generates random samples from this distribution using the specified random generator.
    double
    scv()
    Property alias for getSCV
    void
    setNumParams(int num)
    Sets the number of parameters for this distribution.
    void
    setParam(int id, String name, Object value)
    Sets a parameter value for this distribution.
    double
    skewness()
    Property alias for getSkewness
    Pair<Double,Double>
    support()
    Property alias for getSupport
    double
    var()
    Property alias for getVar

    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

    • mean

      protected double mean

    • immediate

      protected boolean immediate

    • name

      protected String name

    • numParam

      protected int numParam

    • support

      protected Pair<Double,Double> support

    • params

      protected List<NamedParam> params

  • Constructor Details

    • Distribution

      public Distribution(String name, int numParam, Pair<Double,Double> support)
      Creates a new distribution with the specified characteristics.
      Parameters:
      name - the name of this distribution type
      numParam - the number of parameters required
      support - the support range [min, max] for this distribution

  • Method Details

    • evalCDF

      public abstract double evalCDF(double t)
      Evaluates the cumulative distribution function (CDF) at the given point.
      Parameters:
      t - the point at which to evaluate the CDF
      Returns:
      the CDF value at point t

    • evalProbInterval

      public double evalProbInterval(double t0, double t1)
      Evaluates the probability of the distribution falling within the given interval. Computes P(t0 <= X <= t1) = F(t1) - F(t0).
      Parameters:
      t0 - the lower bound of the interval
      t1 - the upper bound of the interval
      Returns:
      the probability of falling within [t0, t1]
      Throws:
      RuntimeException - if t1 < t0

    • getMean

      public abstract double getMean()
      Gets the mean (expected value) of this distribution.
      Returns:
      the mean value

    • getName

      public String getName()
      Gets the name of this distribution type.
      Returns:
      the distribution name

    • getFeatureName

      public String getFeatureName()
      The registry name this distribution is marked under by Network.getUsedLangFeatures(). Separate from getName() because that one also resolves the ProcessType and drives the JSON wire type: a subclass whose feature name is more specific than its process type -- a Trace, or a two-phase Coxian -- must be able to say so to the feature gate without moving to a different process type. Defaults to getName(), so a distribution that needs no distinction inherits the old behaviour.
      Returns:
      the FeatureSet entry naming this distribution

    • getNumParams

      public int getNumParams(int id)
      Gets the number of parameters for this distribution.
      Parameters:
      id - parameter identifier (currently unused)
      Returns:
      the number of parameters

    • getNumParams

      public int getNumParams()
      Gets the number of parameters of this distribution, twin of the MATLAB getNumParams(), which reports length(params).
      Returns:
      the number of parameters

    • getParam

      public NamedParam getParam(int id)
      Gets a parameter by its ID.
      Parameters:
      id - the parameter ID (1-based index)
      Returns:
      the named parameter at the specified position

    • getRate

      public double getRate()
      Gets the rate of this distribution (inverse of mean).
      Returns:
      the rate value (1/mean)

    • getSCV

      public abstract double getSCV()
      Gets the squared coefficient of variation (SCV) of this distribution. SCV = Var(X) / E[X]^2.
      Returns:
      the squared coefficient of variation

    • getSkewness

      public abstract double getSkewness()
      Gets the skewness of this distribution. Skewness measures the asymmetry of the probability distribution.
      Returns:
      the skewness value

    • getSupport

      public Pair<Double,Double> getSupport()
      Gets the support range of this distribution.
      Returns:
      a pair containing [min, max] values where the distribution is defined

    • getVar

      public double getVar()
      Gets the variance of this distribution. Computed as SCV * mean^2.
      Returns:
      the variance

    • isContinuous

      public boolean isContinuous()
      Checks if this is a continuous distribution.
      Returns:
      true if this is a continuous distribution, false otherwise

    • isDisabled

      public boolean isDisabled()
      Checks if this is a disabled distribution.
      Returns:
      true if this is a disabled distribution, false otherwise

    • isDiscrete

      public boolean isDiscrete()
      Checks if this is a discrete distribution.
      Returns:
      true if this is a discrete distribution, false otherwise

    • isImmediate

      public boolean isImmediate()
      Checks if this distribution has immediate (zero) service time.
      Returns:
      true if the distribution is immediate or has mean < Zero threshold

    • sample

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

    • sample

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

    • setNumParams

      public void setNumParams(int num)
      Sets the number of parameters for this distribution.
      Parameters:
      num - the number of parameters

    • setParam

      public void setParam(int id, String name, Object value)
      Sets a parameter value for this distribution.
      Parameters:
      id - the parameter ID (1-based index)
      name - the parameter name
      value - the parameter value

    • getParam

      public NamedParam getParam(String name)
      Returns the parameter carrying a given name, twin of reading the MATLAB params cell by its paramName field.
      Parameters:
      name - the parameter name
      Returns:
      the parameter, or null when no parameter carries that name

    • hasParam

      public boolean hasParam(int id)
      Tests whether a parameter has been set at the given position, i.e. whether it still holds the placeholder installed by the constructor.
      Parameters:
      id - the parameter id (1-based)
      Returns:
      true when the parameter has been assigned

    • getParams

      public List<NamedParam> getParams()
      Returns every parameter of this distribution, in declaration order. The values are the stored objects, so a matrix-valued parameter (a PH representation, a MAP block) is returned as it is held rather than coerced to a scalar.
      Returns:
      the parameter list

    • evalLST

      public abstract double evalLST(double s)
      Evaluate the Laplace-Stieltjes Transform at s
      Parameters:
      s - the Laplace domain variable
      Returns:
      the LST value at s

    • evalLST

      public org.apache.commons.math3.complex.Complex evalLST(org.apache.commons.math3.complex.Complex s)
      Evaluate the Laplace-Stieltjes Transform at a COMPLEX argument. A transform is evaluated off the real axis by everything that inverts it or locates its roots: the Abate-Whitt Euler sum walks a vertical line, and the matrix transform int exp(Ut) dF(t) is read off the spectrum of U, which is complex in general. The real evalLST(double) cannot serve either. This default is the Riemann-Stieltjes sum over the law's own CDF with complex exponentials: the weights are true probability increments, so it is a proper measure for ANY law, including one with an atom or with no density at all. Subclasses that own a closed form override it; the phase-type families do so in Markovian.
      Parameters:
      s - the Laplace domain variable
      Returns:
      the LST value at s

    • isMarkovian

      public boolean isMarkovian()
      Check if this distribution is Markovian (has a matrix process representation)
      Returns:
      true if this is a Markovian distribution, false otherwise

    • name

      public String name()
      Property alias for getName

    • mean

      public double mean()
      Property alias for getMean

    • rate

      public double rate()
      Property alias for getRate

    • scv

      public double scv()
      Property alias for getSCV

    • skewness

      public double skewness()
      Property alias for getSkewness

    • var

      public double var()
      Property alias for getVar

    • support

      public Pair<Double,Double> support()
      Property alias for getSupport

    • numParams

      public int numParams(int id)
      Property alias for getNumParams(int id)

    • param

      public NamedParam param(int id)
      Property alias for getParam(int id)