The LMM PF is a methodology for solving the state and parameter estimation problem for ODEs system, rooted into a Bayesian framework and for it we consider a test problem with known solution to investigate in depth the error sources and how they depend on the choice of LMM used for the numerical integration. We conclude by looking at the effect on the error of replacing LMM with Runge-Kutta (RK) class integration methods.

Computational issues in linear multistep method particle filtering / Calvetti, Daniela; Cuomo, Salvatore; Pragliola, Monica; Somersalo, ERKKI JAAKKO; Toraldo, Gerardo. - 1776:(2016), p. 040009. (Intervento presentato al convegno 2nd International Conference on Numerical Computations: Theory and Algorithms, NUMTA 2016 tenutosi a ita nel 2016) [10.1063/1.4965321].

Computational issues in linear multistep method particle filtering

CALVETTI, DANIELA;CUOMO, SALVATORE;Pragliola, Monica;SOMERSALO, ERKKI JAAKKO;TORALDO, GERARDO
2016

Abstract

The LMM PF is a methodology for solving the state and parameter estimation problem for ODEs system, rooted into a Bayesian framework and for it we consider a test problem with known solution to investigate in depth the error sources and how they depend on the choice of LMM used for the numerical integration. We conclude by looking at the effect on the error of replacing LMM with Runge-Kutta (RK) class integration methods.
2016
9780735414389
9780735414389
Computational issues in linear multistep method particle filtering / Calvetti, Daniela; Cuomo, Salvatore; Pragliola, Monica; Somersalo, ERKKI JAAKKO; Toraldo, Gerardo. - 1776:(2016), p. 040009. (Intervento presentato al convegno 2nd International Conference on Numerical Computations: Theory and Algorithms, NUMTA 2016 tenutosi a ita nel 2016) [10.1063/1.4965321].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/661845
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