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EmrysFilter 0.1.0
State estimation utilities in C++23 using Eigen
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The emission model of the time from one event to the next, from a Poisson process whose rate is a function of the value. More...
#include <EmrysFilter/Models/Emission.h>
Public Types | |
| using | Scalar = Scalar_ |
| the scalar type of the rates | |
Public Member Functions | |
| template<typename Derived> | |
| ExponentialEmission (Eigen::DenseBase< Derived > const &rates, TimeStep< Scalar_ > auto const &tau) | |
| The emission of an inter-arrival time of tau, any TimeStep (see Time steps), with rates one per value. | |
| Scalar_ | interval () const |
| void | logLikelihoods (Space const &space, EmissionBuffer< Space, Scalar > out) const |
| Writes the exponential log-density of the inter-arrival time under each value's rate into out. | |
The emission model of the time from one event to the next, from a Poisson process whose rate is a function of the value.
The exponential density of an inter-arrival time \( \tau \): \( \log p(\tau \mid v) = \log \lambda_v - \lambda_v \tau \). Like PoissonEmission, it treats the value as fixed over the interval; ArrivalInterval is the exact observation over a ContinuousTimeMarkovChain.
| Space | the discrete space |
| Scalar_ | scalar type of the rates, double by default |
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inlinenodiscard |