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SSJ V. 2.6. |
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java.lang.Object umontreal.iro.lecuyer.probdistmulti.DiscreteDistributionIntMulti
public abstract class DiscreteDistributionIntMulti
Classes implementing multi-dimensional discrete distributions over the integers should inherit from this class. It specifies the signature of methods for computing the mass function (or probability) p(x1, x2,…, xd) = P[X1 = x1, X2 = x2,…, Xd = xd] and the cumulative probabilities for a random vector X with a discrete distribution over the integers.
Constructor Summary | |
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DiscreteDistributionIntMulti()
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Method Summary | |
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double |
cdf(int[] x)
Computes the cumulative probability function F of the distribution evaluated at x, assuming the lowest values start at 0, i.e. |
abstract double[][] |
getCorrelation()
Returns the correlation matrix of the distribution, defined as ρij = σij/(σ_iiσ_jj)1/2. |
abstract double[][] |
getCovariance()
Returns the variance-covariance matrix of the distribution, defined as σij = E[(Xi - μi)(Xj - μj)]. |
int |
getDimension()
Returns the dimension d of the distribution. |
abstract double[] |
getMean()
Returns the mean vector of the distribution, defined as μi = E[Xi]. |
abstract double |
prob(int[] x)
Returns the probability mass function p(x1, x2,…, xd), which should be a real number in [0, 1]. |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public DiscreteDistributionIntMulti()
Method Detail |
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public abstract double prob(int[] x)
x
- value at which the mass function must be evaluated
public double cdf(int[] x)
public int getDimension()
public abstract double[] getMean()
public abstract double[][] getCovariance()
public abstract double[][] getCorrelation()
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SSJ V. 2.6. |
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