Robust and Efficient Joint Data Reconciliation – Parameter Estimation Using a Generalized Objective Function
نویسندگان
چکیده
This paper proposes the use of a generalized distribution, namely the Generalized T (GT) distribution in the joint estimation of process states and model parameters. The desirable properties of the GT-based estimator are its robustness, simplicity, flexibility and efficiency for the wide range of commonly encountered distributions (including Box-Tiao and t-distributions) which belong to the GT distribution family. To achieve the efficiency, the parameters of the GT distribution are adapted from the data through preliminary estimation. The strategy is applied to the virtual version of a practical chemical engineering plant. Copyright © 2003 IFAC
منابع مشابه
Parameter Estimation in Spatial Generalized Linear Mixed Models with Skew Gaussian Random Effects using Laplace Approximation
Spatial generalized linear mixed models are used commonly for modelling non-Gaussian discrete spatial responses. We present an algorithm for parameter estimation of the models using Laplace approximation of likelihood function. In these models, the spatial correlation structure of data is carried out by random effects or latent variables. In most spatial analysis, it is assumed that rando...
متن کاملA Two-Phase Robust Estimation of Process Dispersion Using M-estimator
Parameter estimation is the first step in constructing any control chart. Most estimators of mean and dispersion are sensitive to the presence of outliers. The data may be contaminated by outliers either locally or globally. The exciting robust estimators deal only with global contamination. In this paper a robust estimator for dispersion is proposed to reduce the effect of local contamination ...
متن کاملEfficient Estimation of the Density and Cumulative Distribution Function of the Generalized Rayleigh Distribution
The uniformly minimum variance unbiased (UMVU), maximum likelihood, percentile (PC), least squares (LS) and weighted least squares (WLS) estimators of the probability density function (pdf) and cumulative distribution function are derived for the generalized Rayleigh distribution. This model can be used quite effectively in modelling strength data and also modeling general lifetime data. It has...
متن کاملBayes, E-Bayes and Robust Bayes Premium Estimation and Prediction under the Squared Log Error Loss Function
In risk analysis based on Bayesian framework, premium calculation requires specification of a prior distribution for the risk parameter in the heterogeneous portfolio. When the prior knowledge is vague, the E-Bayesian and robust Bayesian analysis can be used to handle the uncertainty in specifying the prior distribution by considering a class of priors instead of a single prior. In th...
متن کاملRobust H_∞ Controller design based on Generalized Dynamic Observer for Uncertain Singular system with Disturbance
This paper presents a robust ∞_H controller design, based on a generalized dynamic observer for uncertain singular systems in the presence of disturbance. The controller guarantees that the closed loop system be admissible. The main advantage of this method is that the uncertainty can be found in the system, the input and the output matrices. Also the generalized dynamic observer is used to est...
متن کامل