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java.lang.Objectde.unihalle.informatik.MiToBo.math.distributions.impl.GaussianDistribution
public class GaussianDistribution
A multivariate Gaussian distribution.
Field Summary | |
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protected Jama.Matrix |
cov
covariance matrix |
protected Jama.Matrix |
icov
inverse covariance matrix |
protected Jama.Matrix |
L
|
protected double |
logfactor
log of the normalization factor |
protected Jama.Matrix |
mean
mean vector |
protected double |
normfactor
normalization factor |
protected java.util.Random |
rand
random generator for sampling |
Constructor Summary | |
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protected |
GaussianDistribution(int DOF)
Constructor for a Gaussian distribution of dimension DOF with the zero vector as mean, the unity matrix as covariance matrix and a new random generator for sampling |
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GaussianDistribution(int DOF,
java.util.Random rand)
Constructor for a Gaussian distribution of dimension DOF with the zero vector as mean, the unity matrix as covariance matrix and a given random generator for sampling |
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GaussianDistribution(Jama.Matrix mean,
Jama.Matrix covariance)
Gaussian distribution with given mean, covariance and a new random generator for sampling |
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GaussianDistribution(Jama.Matrix mean,
Jama.Matrix covariance,
java.util.Random rand)
Gaussian distribution with given mean, covariance and random generator for sampling |
Method Summary | |
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GaussianDistribution |
copy()
|
Jama.Matrix |
drawSample()
Generate a new sample from this density. |
Jama.Matrix |
getCovariance()
Returns the covariance matrix |
Jama.Matrix |
getInverseCovariance()
|
Jama.Matrix |
getMean()
Returns the mean vector. |
double |
log_p(Jama.Matrix x)
Evaluate natural logarithm of p(X) at location x. log(P(X=x)) |
double |
mahalanobis(Jama.Matrix x)
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double |
p(Jama.Matrix x)
Evaluate p(X) at location x. |
void |
setCovariance(Jama.Matrix covariance)
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void |
setMean(Jama.Matrix mean)
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Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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protected Jama.Matrix cov
protected Jama.Matrix icov
protected Jama.Matrix L
protected double logfactor
protected Jama.Matrix mean
protected double normfactor
protected java.util.Random rand
Constructor Detail |
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protected GaussianDistribution(int DOF)
DOF
- public GaussianDistribution(int DOF, java.util.Random rand)
DOF
- rand
- public GaussianDistribution(Jama.Matrix mean, Jama.Matrix covariance) throws java.lang.IllegalArgumentException
mean
- covariance
-
java.lang.IllegalArgumentException
public GaussianDistribution(Jama.Matrix mean, Jama.Matrix covariance, java.util.Random rand) throws java.lang.IllegalArgumentException
mean
- covariance
- rand
-
java.lang.IllegalArgumentException
Method Detail |
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public GaussianDistribution copy()
copy
in interface Copyable<GaussianDistribution>
public Jama.Matrix drawSample()
SamplingDistribution
drawSample
in interface SamplingDistribution<Jama.Matrix>
public Jama.Matrix getCovariance()
getCovariance
in interface SecondOrderCentralMoment<Jama.Matrix>
public Jama.Matrix getInverseCovariance()
public Jama.Matrix getMean()
getMean
in interface FirstOrderMoment<Jama.Matrix>
public double log_p(Jama.Matrix x)
LogEvaluatableDistribution
log_p
in interface LogEvaluatableDistribution<Jama.Matrix>
x
- realization of random variable X
public double mahalanobis(Jama.Matrix x)
public double p(Jama.Matrix x)
EvaluatableDistribution
p
in interface EvaluatableDistribution<Jama.Matrix>
x
- realization of random variable X
public void setCovariance(Jama.Matrix covariance) throws java.lang.IllegalArgumentException
java.lang.IllegalArgumentException
public void setMean(Jama.Matrix mean) throws java.lang.IllegalArgumentException
java.lang.IllegalArgumentException
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