On the first order regression procedure of estimation for incomplete regression models

On the First Order Regression Procedure of Estimation for Incomplete Regression Models

This article discusses some properties of the rst order regression method for imputation of missing values on an explanatory variable in linear regression model and presents an estimation strategy based on hy pothesis testing

On the First Order Regression Procedure

This article discusses some properties of the rst order regression method for imputation of missing values on an explanatory variable in linear regression model and presents an estimation strategy based on hypothesis testing.

Estimation of Parameters in Multiple Regression With Missing X-Observations using Modified First Order Regression Procedure

This paper considers the estimation of coe cients in a linear regression model with missing observations in the independent variables and intro duces a modi cation of the standard rst order regression method for imputation of missing values The modi cation provides stochastic values for imputation Asymptotic properties of the estimators for the regression coe cients arising from the proposed mo...

Derivation of regression models for pan evaporation estimation

Evaporation is an essential component of hydrological cycle. Several meteorologicalfactors play role in the amount of pan evaporation. These factors are often related to eachother. In this study, a multiple linear regression (MLR) in conjunction with PrincipalComponent Analysis (PCA) was used for modeling of pan evaporation. After thestandardization of the variables, independent components were...

An M-Estimation-Based Procedure for Determining the Number of Regression Models in Regression Clustering