AbstractMultivariateRealDistribution
, MixtureMultivariateNormalDistribution
, MixtureMultivariateRealDistribution
, MultivariateNormalDistribution
public interface MultivariateRealDistribution
This is based largely on the RealDistribution interface, but cumulative distribution functions are not required because they are often quite difficult to compute for multivariate distributions.
Modifier and Type | Method | Description |
---|---|---|
double |
density(double[] x) |
Returns the probability density function (PDF) of this distribution
evaluated at the specified point
x . |
int |
getDimension() |
Gets the number of random variables of the distribution.
|
void |
reseedRandomGenerator(long seed) |
Reseeds the random generator used to generate samples.
|
double[] |
sample() |
Generates a random value vector sampled from this distribution.
|
double[][] |
sample(int sampleSize) |
Generates a list of a random value vectors from the distribution.
|
double density(double[] x)
x
. In general, the PDF is the
derivative of the cumulative distribution function. If the derivative
does not exist at x
, then an appropriate replacement should be
returned, e.g. Double.POSITIVE_INFINITY
, Double.NaN
, or
the limit inferior or limit superior of the difference quotient.x
- Point at which the PDF is evaluated.x
.void reseedRandomGenerator(long seed)
seed
- Seed with which to initialize the random number generator.int getDimension()
sample
method.double[] sample()
double[][] sample(int sampleSize) throws MathIllegalArgumentException
sampleSize
- the number of random vectors to generate.MathIllegalArgumentException
- if sampleSize
is not positive.sample()
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