MultivariateGaussian.SufficientStatisticCovarianceInverse (Cognitive Foundry)

java.lang.Object
- gov.sandia.cognition.util.AbstractCloneableSerializable
- - gov.sandia.cognition.statistics.AbstractSufficientStatistic<Vector,MultivariateGaussian>
  - - gov.sandia.cognition.statistics.distribution.MultivariateGaussian.SufficientStatisticCovarianceInverse

All Implemented Interfaces:

Factory<MultivariateGaussian>, SufficientStatistic<Vector,MultivariateGaussian>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

MultivariateGaussian
```
@PublicationReference(author="Wikipedia",
                      title="Sherman\u2013Morrison formula",
                      type=WebPage,
                      year=2011,
                      url="http://en.wikipedia.org/wiki/Sherman%E2%80%93Morrison_formula")
public static class MultivariateGaussian.SufficientStatisticCovarianceInverse
extends AbstractSufficientStatistic<Vector,MultivariateGaussian>
```
Implements the sufficient statistics of the MultivariateGaussian while estimating the inverse of the covariance matrix. This is only slightly more computationally intensive than estimating the covariance directly, but does not require a single matrix inversion. This is useful when it's the covariance inverse ("precision") that you're interested in.

See Also:

Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`static double`	`DEFAULT_COVARIANCE_INVERSE` Default covariance of the statistics, 99999.99999999999.
`protected double`	`defaultCovarianceInverse` Default covariance inverse of the distribution

Fields inherited from class gov.sandia.cognition.statistics.AbstractSufficientStatistic
count

Constructor Summary

Constructors
Constructor and Description
`SufficientStatisticCovarianceInverse()` Default constructor
`SufficientStatisticCovarianceInverse(double defaultCovarianceInverse)` Creates a new instance of SufficientStatisticCovarianceInverse

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`clear()` Resets this set of sufficient statistics to its empty state.
`MultivariateGaussian.SufficientStatisticCovarianceInverse`	`clone()` This makes public the clone method on the `Object` class and removes the exception that it throws.
`MultivariateGaussian.PDF`	`create()` Creates a new instance of an object.
`void`	`create(MultivariateGaussian distribution)` Modifies the given distribution with the parameters indicated by the sufficient statistics
`Matrix`	`getCovarianceInverse()` Gets the covariance Inverse of the Gaussian.
`double`	`getDefaultCovarianceInverse()` Getter for defaultCovarianceInverse
`Vector`	`getMean()` Getter for mean
`Matrix`	`getSumSquaredDifferencesInverse()` Getter for sumSquaredDifferences
`void`	`setDefaultCovariance(double defaultCovarianceInverse)` Setter for defaultCovarianceInverse
`void`	`update(Vector value)` Updates the sufficient statistics from the given value

Methods inherited from class gov.sandia.cognition.statistics.AbstractSufficientStatistic
getCount, setCount, update

Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - DEFAULT_COVARIANCE_INVERSE
```
public static final double DEFAULT_COVARIANCE_INVERSE
```
    Default covariance of the statistics, 99999.99999999999.
    
    See Also:
    
    Constant Field Values
  - defaultCovarianceInverse
```
protected double defaultCovarianceInverse
```
    Default covariance inverse of the distribution
- Constructor Detail
  - SufficientStatisticCovarianceInverse
```
public SufficientStatisticCovarianceInverse()
```
    Default constructor
  - SufficientStatisticCovarianceInverse
```
public SufficientStatisticCovarianceInverse(double defaultCovarianceInverse)
```
    Creates a new instance of SufficientStatisticCovarianceInverse
    
    Parameters:
    
    defaultCovarianceInverse - Default covariance inverse of the distribution
- Method Detail
  - clone
```
public MultivariateGaussian.SufficientStatisticCovarianceInverse clone()
```
    Description copied from class: AbstractCloneableSerializable
    
    This makes public the clone method on the Object class and removes the exception that it throws. Its default behavior is to automatically create a clone of the exact type of object that the clone is called on and to copy all primitives but to keep all references, which means it is a shallow copy. Extensions of this class may want to override this method (but call super.clone() to implement a "smart copy". That is, to target the most common use case for creating a copy of the object. Because of the default behavior being a shallow copy, extending classes only need to handle fields that need to have a deeper copy (or those that need to be reset). Some of the methods in ObjectUtil may be helpful in implementing a custom clone method. Note: The contract of this method is that you must use super.clone() as the basis for your implementation.
    
    Specified by:
    
    clone in interface CloneableSerializable
    
    Overrides:
    
    clone in class AbstractSufficientStatistic<Vector,MultivariateGaussian>
    
    Returns:
    
    A clone of this object.
  - clear
```
public void clear()
```
    Resets this set of sufficient statistics to its empty state.
  - update
```
public void update(Vector value)
```
    Description copied from interface: SufficientStatistic
    
    Updates the sufficient statistics from the given value
    
    Parameters:
    
    value - Value to update the sufficient statistics
  - create
```
public MultivariateGaussian.PDF create()
```
    Description copied from interface: Factory
    
    Creates a new instance of an object.
    
    Returns:
    
    A newly created object.
  - create
```
public void create(MultivariateGaussian distribution)
```
    Description copied from interface: SufficientStatistic
    
    Modifies the given distribution with the parameters indicated by the sufficient statistics
    
    Parameters:
    
    distribution - Distribution to modify by side effect
  - getDefaultCovarianceInverse
```
public double getDefaultCovarianceInverse()
```
    Getter for defaultCovarianceInverse
    
    Returns:
    
    Default covariance Inverse of the distribution
  - setDefaultCovariance
```
public void setDefaultCovariance(double defaultCovarianceInverse)
```
    Setter for defaultCovarianceInverse
    
    Parameters:
    
    defaultCovarianceInverse - Default covariance Inverse of the distribution
  - getMean
```
public Vector getMean()
```
    Getter for mean
    
    Returns:
    
    The mean of the Gaussian
  - getSumSquaredDifferencesInverse
```
public Matrix getSumSquaredDifferencesInverse()
```
    Getter for sumSquaredDifferences
    
    Returns:
    
    This is the sum-squared differences
  - getCovarianceInverse
```
public Matrix getCovarianceInverse()
```
    Gets the covariance Inverse of the Gaussian.
    
    Returns:
    
    The covariance.

Class MultivariateGaussian.SufficientStatisticCovarianceInverse

Field Summary

Fields inherited from class gov.sandia.cognition.statistics.AbstractSufficientStatistic

Constructor Summary

Method Summary

Methods inherited from class gov.sandia.cognition.statistics.AbstractSufficientStatistic

Methods inherited from class java.lang.Object

Field Detail

DEFAULT_COVARIANCE_INVERSE

defaultCovarianceInverse

Constructor Detail

SufficientStatisticCovarianceInverse

SufficientStatisticCovarianceInverse

Method Detail

clone

clear

update

create

create

getDefaultCovarianceInverse

setDefaultCovariance

getMean

getSumSquaredDifferencesInverse

getCovarianceInverse