java.lang.Object
- jsl.utilities.distributions.Distribution
- - jsl.utilities.distributions.Geometric

All Implemented Interfaces:

ControllableIfc, CDFIfc, DiscreteDistributionIfc, DistributionFunctionIfc, DistributionIfc, FirstOrderLossFunctionIfc, InverseCDFIfc, LossFunctionDistributionIfc, MeanIfc, PMFIfc, SecondOrderLossFunctionIfc, VarianceIfc, GetNameIfc, IdentityIfc, NewInstanceIfc, ParametersIfc, GetRVariableIfc
```
public class Geometric
extends Distribution
implements DiscreteDistributionIfc, LossFunctionDistributionIfc, GetRVariableIfc
```
The geometric distribution is the probability distribution of the number Y = X − 1 of failures before the first success, supported on the set { 0, 1, 2, 3, ... }, where X is the number of Bernoulli trials needed to get one success.

Nested Class Summary
- Nested classes/interfaces inherited from class jsl.utilities.distributions.Distribution
  Distribution.RandomControls

Field Summary
- Fields inherited from class jsl.utilities.distributions.Distribution
  myId, myName

Constructor Summary

Constructors
Constructor	Description
`Geometric()`	Constructs a Geometric with success probability = 0.5
`Geometric(double prob)`	Constructs a Geometric using the supplied success probability
`Geometric(double[] parameters)`	Constructs a Geometric using the supplied parameters array parameters[0] is probability of success
`Geometric(double prob, java.lang.String name)`	Constructs a Geometric using the supplied success probability and lower range

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`static boolean`	`canMatchMoments(double... moments)`
`double`	`cdf(double x)`	computes the cdf of the distribution F(X<=x)
`static Geometric`	`createFromMoments(double... moments)`
`double`	`firstOrderLossFunction(double x)`	Computes the first order loss function for the function for given value of x, G1(x) = E[max(X-x,0)]
`double`	`getMean()`	Returns the mean or expected value of a distribution
`double[]`	`getParameters()`	Gets the parameters as an array parameters[0] is probability of success
`static double[]`	`getParametersFromMoments(double... moments)`
`double`	`getProbabilityOfSuccess()`	Gets the probability of success
`RVariableIfc`	`getRandomVariable(RNStreamIfc rng)`
`double`	`getVariance()`	Returns the variance of the distribution if defined
`double`	`invCDF(double prob)`	Gets the inverse cdf for the distribution
`Geometric`	`newInstance()`	Returns a new instance
`double`	`pmf(double x)`	If x is not and integer value, then the probability must be zero otherwise pmf(int x) is used to determine the probability
`double`	`pmf(int x)`	computes the pmf of the distribution f(x) = p(1-p)^(x) for x>=0, 0 otherwise
`double`	`secondOrderLossFunction(double x)`	Computes the 2nd order loss function for the distribution function for given value of x, G2(x) = (1/2)E[max(X-x,0)*max(X-x-1,0)]
`void`	`setParameters(double[] parameters)`	Sets the parameters using the supplied array parameters[0] is probability of success parameters[1] is lower range
`void`	`setProbabilityOfSuccess(double prob)`	Sets the probability of success

Methods inherited from class jsl.utilities.distributions.Distribution
getControls, getId, getName, getStandardDeviation, inverseContinuousCDFViaBisection, inverseContinuousCDFViaBisection, inverseDiscreteCDFViaSearchUp, setControls, setId, setName, toString

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface jsl.utilities.distributions.CDFIfc
cdf, complementaryCDF

Methods inherited from interface jsl.utilities.random.rvariable.GetRVariableIfc
getRandomVariable, getRandomVariable

Methods inherited from interface jsl.utilities.distributions.VarianceIfc
getStandardDeviation

- Constructor Detail
  - Geometric
```
public Geometric()
```
    Constructs a Geometric with success probability = 0.5
  - Geometric
```
public Geometric(double[] parameters)
```
    Constructs a Geometric using the supplied parameters array parameters[0] is probability of success
    
    Parameters:
    
    parameters - the parameter array
  - Geometric
```
public Geometric(double prob)
```
    Constructs a Geometric using the supplied success probability
    
    Parameters:
    
    prob - , the probability of success
  - Geometric
```
public Geometric(double prob,
                 java.lang.String name)
```
    Constructs a Geometric using the supplied success probability and lower range
    
    Parameters:
    
    prob - the probability of success
    
    name - an optional label/name
- Method Detail
  - newInstance
```
public final Geometric newInstance()
```
    Description copied from interface: NewInstanceIfc
    
    Returns a new instance
    
    Specified by:
    
    newInstance in interface NewInstanceIfc
    
    Specified by:
    
    newInstance in class Distribution
    
    Returns:
    
    the new instance
  - setProbabilityOfSuccess
```
public final void setProbabilityOfSuccess(double prob)
```
    Sets the probability of success
    
    Parameters:
    
    prob - the probability of success
  - getProbabilityOfSuccess
```
public final double getProbabilityOfSuccess()
```
    Gets the probability of success
    
    Returns:
    
    the probability of success
  - getMean
```
public final double getMean()
```
    Description copied from interface: MeanIfc
    
    Returns the mean or expected value of a distribution
    
    Specified by:
    
    getMean in interface MeanIfc
    
    Returns:
    
    double the mean or expected value for the distribution
  - getVariance
```
public final double getVariance()
```
    Description copied from interface: VarianceIfc
    
    Returns the variance of the distribution if defined
    
    Specified by:
    
    getVariance in interface VarianceIfc
    
    Returns:
    
    double the variance of the random variable
  - setParameters
```
public final void setParameters(double[] parameters)
```
    Sets the parameters using the supplied array parameters[0] is probability of success parameters[1] is lower range
    
    Specified by:
    
    setParameters in interface ParametersIfc
    
    Parameters:
    
    parameters - the parameter array
  - getParameters
```
public final double[] getParameters()
```
    Gets the parameters as an array parameters[0] is probability of success
    
    Specified by:
    
    getParameters in interface ParametersIfc
    
    Returns:
    
    Returns an array of the parameters
  - pmf
```
public final double pmf(int x)
```
    computes the pmf of the distribution f(x) = p(1-p)^(x) for x>=0, 0 otherwise
    
    Parameters:
    
    x - the value to evaluate
    
    Returns:
    
    the probability
  - pmf
```
public final double pmf(double x)
```
    If x is not and integer value, then the probability must be zero otherwise pmf(int x) is used to determine the probability
    
    Specified by:
    
    pmf in interface PMFIfc
    
    Parameters:
    
    x - the value to evaluate
    
    Returns:
    
    the probability
  - cdf
```
public final double cdf(double x)
```
    computes the cdf of the distribution F(X<=x)
    
    Specified by:
    
    cdf in interface CDFIfc
    
    Parameters:
    
    x - , must be >= lower limit
    
    Returns:
    
    the cumulative probability
  - invCDF
```
public final double invCDF(double prob)
```
    Gets the inverse cdf for the distribution
    
    Specified by:
    
    invCDF in interface InverseCDFIfc
    
    Parameters:
    
    prob - Must be in range [0,1)
    
    Returns:
    
    The inverse cdf evaluated at the supplied probability
  - canMatchMoments
```
public static boolean canMatchMoments(double... moments)
```
  - getParametersFromMoments
```
public static double[] getParametersFromMoments(double... moments)
```
  - createFromMoments
```
public static Geometric createFromMoments(double... moments)
```
  - firstOrderLossFunction
```
public double firstOrderLossFunction(double x)
```
    Description copied from interface: FirstOrderLossFunctionIfc
    
    Computes the first order loss function for the function for given value of x, G1(x) = E[max(X-x,0)]
    
    Specified by:
    
    firstOrderLossFunction in interface FirstOrderLossFunctionIfc
    
    Parameters:
    
    x - The value to be evaluated
    
    Returns:
    
    The loss function value, E[max(X-x,0)]
  - secondOrderLossFunction
```
public double secondOrderLossFunction(double x)
```
    Description copied from interface: SecondOrderLossFunctionIfc
    
    Computes the 2nd order loss function for the distribution function for given value of x, G2(x) = (1/2)E[max(X-x,0)*max(X-x-1,0)]
    
    Specified by:
    
    secondOrderLossFunction in interface SecondOrderLossFunctionIfc
    
    Parameters:
    
    x - The value to be evaluated
    
    Returns:
    
    The loss function value, (1/2)E[max(X-x,0)*max(X-x-1,0)]
  - getRandomVariable
```
public final RVariableIfc getRandomVariable(RNStreamIfc rng)
```
    Specified by:
    
    getRandomVariable in interface GetRVariableIfc
    
    Overrides:
    
    getRandomVariable in class Distribution
    
    Parameters:
    
    rng - the stream to use
    
    Returns:
    
    a random variable

Class Geometric

Nested Class Summary

Nested classes/interfaces inherited from class jsl.utilities.distributions.Distribution

Field Summary

Fields inherited from class jsl.utilities.distributions.Distribution

Constructor Summary

Method Summary

Methods inherited from class jsl.utilities.distributions.Distribution

Methods inherited from class java.lang.Object

Methods inherited from interface jsl.utilities.distributions.CDFIfc

Methods inherited from interface jsl.utilities.random.rvariable.GetRVariableIfc

Methods inherited from interface jsl.utilities.distributions.VarianceIfc

Constructor Detail

Geometric

Geometric

Geometric

Geometric

Method Detail

newInstance

setProbabilityOfSuccess

getProbabilityOfSuccess

getMean

getVariance

setParameters

getParameters

pmf

pmf

cdf

invCDF

canMatchMoments

getParametersFromMoments

createFromMoments

firstOrderLossFunction

secondOrderLossFunction

getRandomVariable