T
- Type of the mixture components.public class MixtureMultivariateRealDistribution<T extends MultivariateRealDistribution> extends AbstractMultivariateRealDistribution
random
Constructor and Description |
---|
MixtureMultivariateRealDistribution(List<Pair<Double,T>> components)
Creates a mixture model from a list of distributions and their
associated weights.
|
MixtureMultivariateRealDistribution(RandomGenerator rng,
List<Pair<Double,T>> components)
Creates a mixture model from a list of distributions and their
associated weights.
|
Modifier and Type | Method and Description |
---|---|
double |
density(double[] values)
Returns the probability density function (PDF) of this distribution
evaluated at the specified point
x . |
List<Pair<Double,T>> |
getComponents()
Gets the distributions that make up the mixture model.
|
void |
reseedRandomGenerator(long seed)
Reseeds the random generator used to generate samples.
|
double[] |
sample()
Generates a random value vector sampled from this distribution.
|
getDimension, sample
public MixtureMultivariateRealDistribution(List<Pair<Double,T>> components)
components
- List of (weight, distribution) pairs from which to sample.public MixtureMultivariateRealDistribution(RandomGenerator rng, List<Pair<Double,T>> components)
rng
- Random number generator.components
- Distributions from which to sample.NotPositiveException
- if any of the weights is negative.DimensionMismatchException
- if not all components have the same
number of variables.public double density(double[] values)
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.values
- Point at which the PDF is evaluated.x
.public double[] sample()
sample
in interface MultivariateRealDistribution
sample
in class AbstractMultivariateRealDistribution
public void reseedRandomGenerator(long seed)
reseedRandomGenerator
in interface MultivariateRealDistribution
reseedRandomGenerator
in class AbstractMultivariateRealDistribution
seed
- Seed with which to initialize the random number generator.Copyright © 2023 CNES. All rights reserved.