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EmrysFilter 0.1.0
State estimation utilities in C++23 using Eigen
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Options for fitMixture(). More...
#include <EmrysFilter/Distributions/Fitting.h>
Public Attributes | |
| int | maxIterations = 100 |
| Maximum number of EM iterations (E-steps). | |
| Scalar | tolerance = Scalar(1e-8) |
| Stop when an iteration improves the weighted log-likelihood by at most this. | |
| Scalar | regularization = Scalar(1e-6) |
| Covariance floor, relative to the source's variance in each dimension: every component covariance gets \( \epsilon \Sigma_{ii} \) added to its \( i \)-th variance. | |
| Scalar | minLogWeight = Scalar(-20) |
| Components whose normalized log-weight falls below this are dropped. | |
Options for fitMixture().
| Scalar Emrys::FitOptions< Scalar >::regularization = Scalar(1e-6) |
Covariance floor, relative to the source's variance in each dimension: every component covariance gets \( \epsilon \Sigma_{ii} \) added to its \( i \)-th variance.
Scaling each dimension by its own variance keeps the floor consistent when the dimensions have different units. Keeps components that capture duplicate particles from collapsing.