Linear Filtering and Recursive Credibility Estimation
نویسنده
چکیده
Recursive credibility estimation is discussed from the viewpoint of linear filtering theory. A conjunction of geometric mterpretation and the innovation approach leads to general algorithms not developed before. Moreover, covariance characterizations considered by other researchers drop our elegantly as a result of geometric considerations. Examples are presented of Kalman type filters valid for non-Gaussian measurements
منابع مشابه
Change Point Estimation of the Stationary State in Auto Regressive Moving Average Models, Using Maximum Likelihood Estimation and Singular Value Decomposition-based Filtering
In this paper, for the first time, the subject of change point estimation has been utilized in the stationary state of auto regressive moving average (ARMA) (1, 1). In the monitoring phase, in case the features of the question pursue a time series, i.e., ARMA(1,1), on the basis of the maximum likelihood technique, an approach will be developed for the estimation of the stationary state’s change...
متن کاملLinear Estimation in ein Spaces- eory
The authors develop a self-contained theory for linear estimation in Krein spaces. The derivation is based on simple concepts such as projections and matrix factorizations and leads to an interesting connection between Krein space projection and the recursive computation of the stationary points of certain second-order (or quadratic) forms. The authors use the innovations process to obtain a ge...
متن کاملApplications of Random Parameter Matrices Kalman Filtering in Uncertain Observation and Multi-Model Systems
This paper considers the Linear Minimum Variance recursive state estimation for the linear discrete time dynamic system with random state transition and measurement matrices, i.e., random parameter matrices Kalman filtering. It is shown that such system can be converted to a linear dynamic system with deterministic parameter matrices but state-dependent process and measurement noises. It is pro...
متن کاملStability of hybrid linear stochastic systems - a technical tool in recursive identification
The identification of continuous-time stochastic systems, in particular recursive estimation, is a basic building block for continuous-time stochastic adaptive filtering and control as well, see the works of Van Schuppen, Duncan and Pasik-Duncan. In these papers the underlying stochastic systems is essentially an AR-system, for which the recursive maximum-likelihood (RML) estimation reduces to ...
متن کاملStatistical Filtering
This paper is a tutorial survey which focuses on some developments introduction in statistical filtering achieved since the of Wiener and Kalman filters for linear gaussian problems. Kalman are reviewed with filters (including reference to their smoothers and predictors) interesting properties and also their fundamental limitations in nonlinear or unknown environments. For nonlinear filtering p...
متن کامل