Implements binomial random variate generators using the convolution method. More...
Inheritance diagram for BinomialConvolutionGen:
Collaboration diagram for BinomialConvolutionGen:
Public Member Functions | |
| BinomialConvolutionGen (RandomStream s, int n, double p) | |
Creates a binomial random variate generator with parameters \(n\) and \(p\), using stream s. | |
| BinomialConvolutionGen (RandomStream s, BinomialDist dist) | |
Creates a random variate generator for the binomial distribution dist and stream s. | |
| int | nextInt () |
 Public Member Functions inherited from BinomialGen | |
| BinomialGen (RandomStream s, int n, double p) | |
Creates a binomial random variate generator with parameters \(n\) and \(p\), using stream s. | |
| BinomialGen (RandomStream s, BinomialDist dist) | |
Creates a random variate generator for the binomial distribution dist and the random stream s. | |
| int | getN () |
| Returns the parameter \(n\) of this object. | |
| double | getP () |
| Returns the parameter \(p\) of this object. | |
| Public Member Functions inherited from RandomVariateGenInt | |
| RandomVariateGenInt (RandomStream s, DiscreteDistributionInt dist) | |
Creates a new random variate generator for the discrete distribution dist, using stream s. More... | |
| int | nextInt () |
| Generates a random number (an integer) from the discrete distribution contained in this object. More... | |
| void | nextArrayOfInt (int[] v, int start, int n) |
Generates n random numbers from the discrete distribution contained in this object. More... | |
| int [] | nextArrayOfInt (int n) |
Generates n random numbers from the discrete distribution contained in this object, and returns them in a new array of size n. More... | |
| DiscreteDistributionInt | getDistribution () |
| Returns the umontreal.ssj.probdist.DiscreteDistributionInt used by this generator. More... | |
| Public Member Functions inherited from RandomVariateGen | |
| RandomVariateGen (RandomStream s, Distribution dist) | |
Creates a new random variate generator from the distribution dist, using stream s. More... | |
| double | nextDouble () |
| Generates a random number from the continuous distribution contained in this object. More... | |
| void | nextArrayOfDouble (double[] v, int start, int n) |
Generates n random numbers from the continuous distribution contained in this object. More... | |
| double [] | nextArrayOfDouble (int n) |
Generates n random numbers from the continuous distribution contained in this object, and returns them in a new array of size n. More... | |
| RandomStream | getStream () |
| Returns the umontreal.ssj.rng.RandomStream used by this generator. More... | |
| void | setStream (RandomStream stream) |
Sets the umontreal.ssj.rng.RandomStream used by this generator to stream. | |
| Distribution | getDistribution () |
| Returns the umontreal.ssj.probdist.Distribution used by this generator. More... | |
| String | toString () |
Returns a String containing information about the current generator. | |
Static Public Member Functions | |
| static int | nextInt (RandomStream s, int n, double p) |
Generates a new integer from the binomial distribution with parameters \(n = \) n and \(p = \) p, using the given stream s. | |
| Static Public Member Functions inherited from BinomialGen | |
| static int | nextInt (RandomStream s, int n, double p) |
Generates a new integer from the binomial distribution with parameters \(n = \) n and \(p = \) p, using the given stream s. | |
Additional Inherited Members | |
| Protected Member Functions inherited from BinomialGen | |
| void | setParams (int n, double p) |
| Sets the parameter \(n\) and \(p\) of this object. | |
| Protected Attributes inherited from BinomialGen | |
| int | n = -1 |
| double | p = -1.0 |
| Protected Attributes inherited from RandomVariateGen | |
| RandomStream | stream |
| Distribution | dist |
Detailed Description
Implements binomial random variate generators using the convolution method.
This method generates \(n\) Bernouilli random variates with parameter \(p\) and adds them up. Its advantages are that it requires little computer memory and no setup time. Its disadvantage is that it is very slow for large \(n\). It makes sense only when \(n\) is small.
The documentation for this class was generated from the following file:
- BinomialConvolutionGen.java
