#include <distribution.h>
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| | MultivariateMixtureDistribution (const std::vector< std::shared_ptr< MultivariateNormalDistribution > > &components, const std::vector< double > &weights) |
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| Eigen::VectorXd | sample (std::default_random_engine &rng) |
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| double | logPDF (const Eigen::Ref< const Eigen::VectorXd > &x) const |
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| size_t | dimension () const |
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| double | logPDF (const Eigen::Ref< const Eigen::VectorXd > &x) const |
| | Computes the joint log probability density function (log-PDF) of the distribution.
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| Eigen::VectorXd | sample (std::default_random_engine &rng) |
| | Draws a single vector sample from the joint distribution.
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| Eigen::MatrixXd | toCanonical (const Eigen::MatrixXd &x) const |
| | Transforms physical samples to standard canonical space.
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| Eigen::MatrixXd | fromCanonical (const Eigen::MatrixXd &x) const |
| | Transforms standard canonical samples back to physical space.
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| size_t | dimension () const |
| | Returns the dimensionality of the multivariate space.
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◆ MultivariateMixtureDistribution()
| cmp::distribution::MultivariateMixtureDistribution::MultivariateMixtureDistribution |
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const std::vector< std::shared_ptr< MultivariateNormalDistribution > > & |
components, |
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const std::vector< double > & |
weights |
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) |
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inline |
◆ dimension()
| size_t cmp::distribution::MultivariateMixtureDistribution::dimension |
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const |
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inline |
◆ logPDF()
| double cmp::distribution::MultivariateMixtureDistribution::logPDF |
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const Eigen::Ref< const Eigen::VectorXd > & |
x | ) |
const |
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inline |
◆ sample()
| Eigen::VectorXd cmp::distribution::MultivariateMixtureDistribution::sample |
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std::default_random_engine & |
rng | ) |
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inline |
◆ components_
Gaussian components of the mixture.
◆ weights_
| std::vector<double> cmp::distribution::MultivariateMixtureDistribution::weights_ |
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private |
Mixing weights for each component.
The documentation for this class was generated from the following file: