Estimation of a Linear Regression Model from Aggregate Means

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)

Efficient Semiparametric Estimation of a Partially Linear Quantile Regression Model

This paper is concerned with estimating a conditional quantile function that is assumed to be partially linear+ The paper develops a simple estimator of the parametric component of the conditional quantile+ The semiparametric efficiency bound for the parametric component is derived, and two types of efficient estimators are considered+ Asymptotic properties of the proposed estimators are establ...

A WEIGHTED LINEAR REGRESSION MODEL FOR IMPERCISE RESPONSE

A weighted linear regression model with impercise response and p-real explanatory variables is analyzed. The LR fuzzy random variable is introduced and a metric is suggested for coping with this kind of variables. A least square solution for estimating the parameters of the model is derived. The result are illustrated by the means of some case studies.

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...