Robustness in parameter estimation

Robustness under Real Parameter Uncertainty

A NEW APPROACH FOR PARAMETER ESTIMATION IN FUZZY LOGISTIC REGRESSION

Logistic regression analysis is used to model categorical dependent variable. It is usually used in social sciences and clinical research. Human thoughts and disease diagnosis in clinical research contain vagueness. This situation leads researchers to combine fuzzy set and statistical theories. Fuzzy logistic regression analysis is one of the outcomes of this combination and it is used in situa...

CREDIBILISTIC PARAMETER ESTIMATION AND ITS APPLICATION IN FUZZY PORTFOLIO SELECTION

In this paper, a maximum likelihood estimation and a minimum entropy estimation for the expected value and variance of normal fuzzy variable are discussed within the framework of credibility theory. As an application, a credibilistic portfolio selection model is proposed, which is an improvement over the traditional models as it only needs the predicted values on the security returns instead of...

Online State Space Model Parameter Estimation in Synchronous Machines

The purpose of this paper is to present a new approach based on the Least Squares Error method for estimating the unknown parameters of the nonlinear 3rd order synchronous generator model. The proposed method uses the mathematical relationships between the machine parameters and on-line input/output measurements to estimate the parameters of the nonlinear state space model. The field voltage is...

Robustness of the Unscented Kalman filter for state and parameter estimation in an elastic transmission

The Unscented Kalman Filter (UKF) was applied to state and parameter estimation of a one degree of freedom robot link with an elastic, cable-driven transmission. Only motor encoder and command torque data was used as input to the filter. The UKF was used offline for joint state and model-parameter estimation, and online for state estimation. This paper presents an analysis of the robustness of ...