Maximum likelihood estimation via the extended covariance and combined square-root filters

DOI10.1016/j.matcom.2008.08.004zbMath1163.65044OpenAlexW1988281543MaRDI QIDQ1005207

M. V. Kulikova

Publication date: 9 March 2009

Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.matcom.2008.08.004

zbMATH Keywords

numerical resultsmaximum likelihood estimationKalman filterSystem identificationdiscrete-time linear stochastic systemsquared-root filtering algorithmssystem sensitive equations

Mathematics Subject Classification ID

Related Items (8)

A feasible implementation procedure for interval analysis method from measurement data ⋮ Differentiating matrix orthogonal transformations ⋮ Stochastic volatility models for exchange rates and their estimation using quasi-maximum-likelihood methods: an application to the South African Rand ⋮ On the computation of derivatives within LD factorization of parametrized matrices ⋮ Computing the gradient of the auxiliary quality functional in the parametric identification problem for stochastic systems ⋮ A unified square-root approach for the score and Fisher information matrix computation in linear dynamic systems ⋮ Constructing numerically stable Kalman filter-based algorithms for gradient-based adaptive filtering ⋮ Maximum likelihood estimation of linear stochastic systems in the class of sequential square-root orthogonal filtering methods

Cites Work

• Unnamed Item
• Score Evaluation Within the Extended Square-Root Information Filter
• Numerical aspects of different Kalman filter implementations
• A new method for evaluating the log-likelihood gradient (score) of linear dynamic systems
• A new method for evaluating the log-likelihood gradient, the Hessian, and the Fisher information matrix for linear dynamic systems
• Computational aspects of maximum likelihood estimation and reduction in sensitivity function calculations
• New square-root algorithms for Kalman filtering
• Maximum likelihood estimation using square root information filters

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