Gaussian.h File Reference

The Gaussian: its parameters GaussianParams, the Gaussian that evaluates the density, read from them by toDensity() (decisions.md [params-and-density]), and the GaussianMarginal view from marginal<Path>() (decisions.md [density-names]), with conditional<Path>(), insert() and erase() on a resizable block, the repair of a covariance that fails to factorize by a Repair such as roots::ridge(), and the exact confidence regions. More...

#include <expected>
#include <optional>
#include <type_traits>
#include <utility>
#include <Eigen/Cholesky>
#include <EmrysFilter/Core/ChiSquared.h>
#include <EmrysFilter/Core/Forwarding.h>
#include <EmrysFilter/Core/Macros.h>
#include <EmrysFilter/Core/Math.h>
#include <EmrysFilter/Core/Print.h>
#include <EmrysFilter/Core/Solve.h>
#include <EmrysFilter/Core/Stamp.h>
#include <EmrysFilter/Distributions/Moments.h>
#include <EmrysFilter/Distributions/Roots.h>
#include <EmrysFilter/Spaces/Composite.h>
#include <EmrysFilter/Spaces/Indexing.h>
#include <EmrysFilter/Spaces/Space.h>
#include <EmrysFilter/Spaces/Subspace.h>
#include <EmrysFilter/Spaces/TagPath.h>

Go to the source code of this file.

Classes
struct	Emrys::GaussianConditional< Space_, Scalar_ >
	The result of GaussianParams::conditionalWithEvidence(): the conditional distribution and the log-evidence of the given values. More...
class	Emrys::GaussianParams< Space_, Scalar_ >
	A Gaussian distribution: a mean and covariance in a space. More...
class	Emrys::Gaussian< Space_, Scalar_ >
	The density of a Gaussian whose covariance has been factorized: a read-only view. More...
class	Emrys::GaussianMarginal< Source, Selection, SubSpace >
	Read-only view of a subset of the entries of a GaussianParams or Gaussian. More...

Detailed Description

The Gaussian: its parameters GaussianParams, the Gaussian that evaluates the density, read from them by toDensity() (decisions.md [params-and-density]), and the GaussianMarginal view from marginal<Path>() (decisions.md [density-names]), with conditional<Path>(), insert() and erase() on a resizable block, the repair of a covariance that fails to factorize by a Repair such as roots::ridge(), and the exact confidence regions.

Every Kalman-family filter holds its parameters. It is the covariance form of the four in decisions.md [gaussian-forms], with the accessors every form shares. GaussianError and the repairs are in Roots.h. Read Sampling.h next.