The Separate Parameter Estimation in Univariate Fuzzy Linear Regression Model

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...

ESTIMATING THE PARAMETERS OF A FUZZY LINEAR REGRESSION MODEL

Fuzzy linear regression models are used to obtain an appropriate linear relation between a dependent variable and several independent variables in a fuzzy environment. Several methods for evaluating fuzzy coefficients in linear regression models have been proposed. The first attempts at estimating the parameters of a fuzzy regression model used mathematical programming methods. In this the...

Comparing The ANN And Linear Regression In Estimation Of The Growth Model (The Case Of MENA)

The Relative Efficiency of Parameter Estimation in Linear Weighted Regression

The research is supported by the Natural Science Foundation of Shandong Province, China (No.ZR2010AL018) Nan Chen and Baoguang Tian are with Mathematics and Physics College of Qingdao University of Science and Technology, China (e-mail: [email protected], [email protected], respectively). 2 2 1 2 1 ( ) ( ) X W X X W WX X W X         .It will bring some losses to the estimation when ...

Robust Estimation in Linear Regression Model: the Density Power Divergence Approach

The minimum density power divergence method provides a robust estimate in the face of a situation where the dataset includes a number of outlier data. In this study, we introduce and use a robust minimum density power divergence estimator to estimate the parameters of the linear regression model and then with some numerical examples of linear regression model, we show the robustness of this est...