DiagonalGaussianDistribution Class Reference

A single multivariate Gaussian distribution with diagonal covariance. More...

## Public Member Functions

DiagonalGaussianDistribution ()
Default constructor, which creates a Gaussian with zero dimension. More...

DiagonalGaussianDistribution (const size_t dimension)
Create a Gaussian Distribution with zero mean and diagonal covariance with the given dimensionality. More...

DiagonalGaussianDistribution (const arma::vec &mean, const arma::vec &covariance)
Create a Gaussian distribution with the given mean and diagonal covariance. More...

const arma::vec & Covariance () const
Return the covariance matrix. More...

void Covariance (const arma::vec &covariance)
Set the covariance matrix. More...

void Covariance (arma::vec &&covariance)
Set the covariance matrix using move assignment. More...

size_t Dimensionality () const
Return the dimensionality of this distribution. More...

double LogProbability (const arma::vec &observation) const
Return the log probability of the given observation. More...

void LogProbability (const arma::mat &observations, arma::vec &logProbabilities) const
Calculate the multivariate Gaussian log probability density function for each data point (column) in the given matrix. More...

const arma::vec & Mean () const
Return the mean. More...

arma::vec & Mean ()
Return a modifiable copy of the mean. More...

double Probability (const arma::vec &observation) const
Return the probability of the given observation. More...

void Probability (const arma::mat &x, arma::vec &probabilities) const
Calculate the multivariate Gaussian probability density function for each data point (column) in the given matrix. More...

arma::vec Random () const
Return a randomly generated observation according to the probability distribution defined by this object. More...

template
<
typename
Archive
>
void serialize (Archive &ar, const uint32_t)
Serialize the distribution. More...

void Train (const arma::mat &observations)
Estimate the Gaussian distribution directly from the given observations. More...

void Train (const arma::mat &observations, const arma::vec &probabilities)
Estimate the Gaussian distribution from the given observations, taking into account the probability of each observation actually being from this distribution. More...

## Detailed Description

A single multivariate Gaussian distribution with diagonal covariance.

Definition at line 21 of file diagonal_gaussian_distribution.hpp.

## ◆ DiagonalGaussianDistribution() [1/3]

 DiagonalGaussianDistribution ( )
inline

Default constructor, which creates a Gaussian with zero dimension.

Definition at line 38 of file diagonal_gaussian_distribution.hpp.

## ◆ DiagonalGaussianDistribution() [2/3]

 DiagonalGaussianDistribution ( const size_t dimension )
inline

Create a Gaussian Distribution with zero mean and diagonal covariance with the given dimensionality.

Parameters
 dimension Number of dimensions.

Definition at line 46 of file diagonal_gaussian_distribution.hpp.

## ◆ DiagonalGaussianDistribution() [3/3]

 DiagonalGaussianDistribution ( const arma::vec & mean, const arma::vec & covariance )

Create a Gaussian distribution with the given mean and diagonal covariance.

Parameters
 mean Mean of distribution. covariance Covariance of distribution.

## ◆ Covariance() [1/3]

 const arma::vec& Covariance ( ) const
inline

Return the covariance matrix.

Definition at line 133 of file diagonal_gaussian_distribution.hpp.

## ◆ Covariance() [2/3]

 void Covariance ( const arma::vec & covariance )

Set the covariance matrix.

## ◆ Covariance() [3/3]

 void Covariance ( arma::vec && covariance )

Set the covariance matrix using move assignment.

## ◆ Dimensionality()

 size_t Dimensionality ( ) const
inline

Return the dimensionality of this distribution.

Definition at line 64 of file diagonal_gaussian_distribution.hpp.

## ◆ LogProbability() [1/2]

 double LogProbability ( const arma::vec & observation ) const

Return the log probability of the given observation.

Referenced by DiagonalGaussianDistribution::Probability().

## ◆ LogProbability() [2/2]

 void LogProbability ( const arma::mat & observations, arma::vec & logProbabilities ) const

Calculate the multivariate Gaussian log probability density function for each data point (column) in the given matrix.

Parameters
 observations Matrix of observations. logProbabilities Output log probabilities for each observation.

## ◆ Mean() [1/2]

 const arma::vec& Mean ( ) const
inline

Return the mean.

Definition at line 127 of file diagonal_gaussian_distribution.hpp.

## ◆ Mean() [2/2]

 arma::vec& Mean ( )
inline

Return a modifiable copy of the mean.

Definition at line 130 of file diagonal_gaussian_distribution.hpp.

## ◆ Probability() [1/2]

 double Probability ( const arma::vec & observation ) const
inline

Return the probability of the given observation.

Definition at line 67 of file diagonal_gaussian_distribution.hpp.

## ◆ Probability() [2/2]

 void Probability ( const arma::mat & x, arma::vec & probabilities ) const
inline

Calculate the multivariate Gaussian probability density function for each data point (column) in the given matrix.

Parameters
 x Matrix of observations. probabilities Output probabilities for each input observation.

Definition at line 82 of file diagonal_gaussian_distribution.hpp.

## ◆ Random()

 arma::vec Random ( ) const

Return a randomly generated observation according to the probability distribution defined by this object.

Returns
Random observation from this Diagonal Gaussian distribution.

Referenced by DiagonalGaussianDistribution::Probability().

## ◆ serialize()

 void serialize ( Archive & ar, const uint32_t )
inline

Serialize the distribution.

Definition at line 143 of file diagonal_gaussian_distribution.hpp.

## ◆ Train() [1/2]

 void Train ( const arma::mat & observations )

Estimate the Gaussian distribution directly from the given observations.

Parameters
 observations Matrix of observations.

Referenced by DiagonalGaussianDistribution::Probability().

## ◆ Train() [2/2]

 void Train ( const arma::mat & observations, const arma::vec & probabilities )

Estimate the Gaussian distribution from the given observations, taking into account the probability of each observation actually being from this distribution.

Parameters
 observations Matrix of observations. probabilities List of probability of the each observation being from this distribution.

The documentation for this class was generated from the following file: