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java.lang.Object umontreal.iro.lecuyer.probdistmulti.ContinuousDistributionMulti umontreal.iro.lecuyer.probdistmulti.DirichletDist
public class DirichletDist
Implements the abstract class ContinuousDistributionMulti
for the
Dirichlet distribution with parameters
(α1,...,αd),
αi > 0.
The probability density is
Constructor Summary | |
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DirichletDist(double[] alpha)
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Method Summary | |
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double |
density(double[] x)
Returns f (x1, x2,…, xd), the probability density of X evaluated at the point x, where x = {x1, x2,…, xd}. |
static double |
density(double[] alpha,
double[] x)
Computes the density of the Dirichlet distribution with parameters (α1, ..., αd). |
double[] |
getAlpha()
Returns the parameters (α1, ..., αd) of this object. |
double |
getAlpha(int i)
Returns the ith component of the alpha vector. |
double[][] |
getCorrelation()
Returns the correlation matrix of the distribution, defined as ρij = σij/(σ_iiσ_jj)1/2. |
static double[][] |
getCorrelation(double[] alpha)
Computes the correlation matrix of the Dirichlet distribution with parameters (α1, ..., αd). |
double[][] |
getCovariance()
Returns the variance-covariance matrix of the distribution, defined as σij = E[(Xi - μi)(Xj - μj)]. |
static double[][] |
getCovariance(double[] alpha)
Computes the covariance matrix of the Dirichlet distribution with parameters (α1, ..., αd). |
double[] |
getMean()
Returns the mean vector of the distribution, defined as μi = E[Xi]. |
static double[] |
getMean(double[] alpha)
Computes the mean E[X] = αi/α0 of the Dirichlet distribution with parameters (α1, ..., αd), where α0 = ∑i=1dαi. |
static double[] |
getMLE(double[][] x,
int n,
int d)
Estimates the parameters [ hat(α_1),…, hat(α_d)] of the Dirichlet distribution using the maximum likelihood method. |
void |
setParams(double[] alpha)
Sets the parameters (α1, ..., αd) of this object. |
Methods inherited from class umontreal.iro.lecuyer.probdistmulti.ContinuousDistributionMulti |
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getDimension |
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 DirichletDist(double[] alpha)
Method Detail |
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public double density(double[] x)
ContinuousDistributionMulti
density
in class ContinuousDistributionMulti
x
- value at which the density is evaluated
public double[] getMean()
ContinuousDistributionMulti
getMean
in class ContinuousDistributionMulti
public double[][] getCovariance()
ContinuousDistributionMulti
getCovariance
in class ContinuousDistributionMulti
public double[][] getCorrelation()
ContinuousDistributionMulti
getCorrelation
in class ContinuousDistributionMulti
public static double density(double[] alpha, double[] x)
public static double[][] getCovariance(double[] alpha)
public static double[][] getCorrelation(double[] alpha)
public static double[] getMLE(double[][] x, int n, int d)
x
- the list of observations to use to evaluate parametersn
- the number of observations to use to evaluate parametersd
- the dimension of each vector
public static double[] getMean(double[] alpha)
public double[] getAlpha()
public double getAlpha(int i)
public void setParams(double[] alpha)
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