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SSJ V. labo. |
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java.lang.Objectumontreal.iro.lecuyer.randvarmulti.RandomMultivariateGen
umontreal.iro.lecuyer.randvarmulti.MultinormalGen
umontreal.iro.lecuyer.randvarmulti.MultinormalCholeskyGen
public class MultinormalCholeskyGen
Extends MultinormalGen for a multivariate normal distribution, generated via a Cholesky decomposition of the covariance
matrix. The covariance matrix
Σ is decomposed (by the constructor)
as
Σ = AAt where A is a lower-triangular matrix
(this is the Cholesky decomposition), and X is generated via
| Constructor Summary | |
|---|---|
MultinormalCholeskyGen(NormalGen gen1,
double[] mu,
double[][] sigma)
Equivalent to MultinormalCholeskyGen(gen1, mu, new DenseDoubleMatrix2D(sigma)). |
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MultinormalCholeskyGen(NormalGen gen1,
double[] mu,
DoubleMatrix2D sigma)
Constructs a multinormal generator with mean vector mu and covariance matrix sigma. |
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| Method Summary | |
|---|---|
DoubleMatrix2D |
getCholeskyDecompSigma()
Returns the lower-triangular matrix A in the Cholesky decomposition of Σ. |
void |
nextPoint(double[] p)
Generates a point from this multinormal distribution. |
static void |
nextPoint(NormalGen gen1,
double[] mu,
double[][] sigma,
double[] p)
Equivalent to nextPoint(gen1, mu, new DenseDoubleMatrix2D(sigma), p). |
static void |
nextPoint(NormalGen gen1,
double[] mu,
DoubleMatrix2D sigma,
double[] p)
Generates a d-dimensional vector from the multinormal distribution with mean vector mu and covariance matrix sigma, using the one-dimensional normal generator gen1 to generate the coordinates of Z, and using the Cholesky decomposition of Σ. |
void |
setSigma(DoubleMatrix2D sigma)
Sets the covariance matrix Σ of this multinormal generator to sigma (and recomputes A). |
| Methods inherited from class umontreal.iro.lecuyer.randvarmulti.MultinormalGen |
|---|
getMu, getMu, getSigma, setMu, setMu |
| Methods inherited from class umontreal.iro.lecuyer.randvarmulti.RandomMultivariateGen |
|---|
getDimension, getStream, nextArrayOfPoints, setStream |
| Methods inherited from class java.lang.Object |
|---|
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public MultinormalCholeskyGen(NormalGen gen1,
double[] mu,
double[][] sigma)
MultinormalCholeskyGen(gen1, mu, new DenseDoubleMatrix2D(sigma)).
gen1 - the one-dimensional generatormu - the mean vector.sigma - the covariance matrix.
NullPointerException - if any argument is null.
IllegalArgumentException - if the length of the mean
vector is incompatible with the dimensions of the covariance matrix.
public MultinormalCholeskyGen(NormalGen gen1,
double[] mu,
DoubleMatrix2D sigma)
gen1 - the one-dimensional generatormu - the mean vector.sigma - the covariance matrix.
NullPointerException - if any argument is null.
IllegalArgumentException - if the length of the mean
vector is incompatible with the dimensions of the covariance matrix.| Method Detail |
|---|
public DoubleMatrix2D getCholeskyDecompSigma()
public void setSigma(DoubleMatrix2D sigma)
sigma - the new covariance matrix.
IllegalArgumentException - if sigma has
incorrect dimensions.
public static void nextPoint(NormalGen gen1,
double[] mu,
double[][] sigma,
double[] p)
nextPoint(gen1, mu, new DenseDoubleMatrix2D(sigma), p).
public static void nextPoint(NormalGen gen1,
double[] mu,
DoubleMatrix2D sigma,
double[] p)
p - the array to be filled with the generated point.
IllegalArgumentException - if the one-dimensional normal
generator uses a normal distribution with μ not equal to 0, or
σ not equal to 1.
IllegalArgumentException - if the length of the mean
vector is different from the dimensions of the covariance matrix,
or if the covariance matrix is not symmetric and positive-definite.
NullPointerException - if any argument is null.public void nextPoint(double[] p)
nextPoint in class MultinormalGenp - the array to be filled with the generated point
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SSJ V. labo. |
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