umontreal.iro.lecuyer.probdist
Class PascalDist
- java.lang.Object
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- umontreal.iro.lecuyer.probdist.DiscreteDistributionInt
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- umontreal.iro.lecuyer.probdist.NegativeBinomialDist
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- umontreal.iro.lecuyer.probdist.PascalDist
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- All Implemented Interfaces:
- Distribution
public class PascalDist extends NegativeBinomialDist
The Pascal distribution is a special case of the negative binomial distribution with parameters n and p, where n is a positive integer and 0 <= p <= 1. Its mass function isp(x) = nCr(n + x - 1, x)pn(1 - p)x, for x = 0, 1, 2,…where nCr is defined inBinomialDist. This p(x) can be interpreted as the probability of having x failures before the nth success in a sequence of independent Bernoulli trials with probability of success p. For n = 1, this gives the geometric distribution.
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Field Summary
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Fields inherited from class umontreal.iro.lecuyer.probdist.NegativeBinomialDist
MAXN
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Fields inherited from class umontreal.iro.lecuyer.probdist.DiscreteDistributionInt
EPSILON
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Constructor Summary
Constructors Constructor and Description PascalDist(int n, double p)Creates an object that contains the probability terms and the distribution function for the Pascal distribution with parameter n and p.
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method and Description static PascalDistgetInstanceFromMLE(int[] x, int m)Creates a new instance of a Pascal distribution with parameters n and p estimated using the maximum likelihood method based on the m observations x[i], i = 0, 1,…, m - 1.static double[]getMLE(int[] x, int m)Estimates the parameter (n, p) of the Pascal distribution using the maximum likelihood method, from the m observations x[i], i = 0, 1,…, m - 1.intgetN()Returns the parameter n of this object.double[]getParams()Return a table containing the parameters of the current distribution.voidsetParams(int n, double p)Sets the parameter n and p of this object.java.lang.StringtoString()-
Methods inherited from class umontreal.iro.lecuyer.probdist.NegativeBinomialDist
barF, cdf, cdf, getGamma, getInstanceFromMLE, getInstanceFromMLE1, getMean, getMean, getMLE, getMLE1, getP, getStandardDeviation, getStandardDeviation, getVariance, getVariance, inverseF, inverseFInt, prob, prob, setParams
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Constructor Detail
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PascalDist
public PascalDist(int n, double p)Creates an object that contains the probability terms and the distribution function for the Pascal distribution with parameter n and p.
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Method Detail
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getMLE
public static double[] getMLE(int[] x, int m)Estimates the parameter (n, p) of the Pascal distribution using the maximum likelihood method, from the m observations x[i], i = 0, 1,…, m - 1. The estimates are returned in a two-element array, in regular order: [n, p].- Parameters:
x- the list of observations used to evaluate parametersm- the number of observations used to evaluate parameters- Returns:
- returns the parameters [hat(n), hat(p)]
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getInstanceFromMLE
public static PascalDist getInstanceFromMLE(int[] x, int m)
Creates a new instance of a Pascal distribution with parameters n and p estimated using the maximum likelihood method based on the m observations x[i], i = 0, 1,…, m - 1.- Parameters:
x- the list of observations to use to evaluate parametersm- the number of observations to use to evaluate parameters
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getN
public int getN()
Returns the parameter n of this object.
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setParams
public void setParams(int n, double p)Sets the parameter n and p of this object.
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getParams
public double[] getParams()
Return a table containing the parameters of the current distribution. This table is put in regular order: [n, p].- Specified by:
getParamsin interfaceDistribution- Overrides:
getParamsin classNegativeBinomialDist
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toString
public java.lang.String toString()
- Overrides:
toStringin classNegativeBinomialDist
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