Estimating A Semi - Parametric Partial Linear Regression Model with Different Estimation Methods with Incomplete Data
Abstract
The regression method is used to measure the relationship between two variables in the form of a function, for the relationship between a dependent variable, which is related to one or explanatory variables. In this research, a parasympathetic partial linear regression model that represents the median state between the parameter regression model and the Non-parametric regression model has found wide acceptance in many Among the studies where methods of estimating a developer have been used to estimate the semi-linear partial linear regression model with a loss in the parameter part represented by the MCBEM model calibration method in addition to the MCB model calibration method proposed by the researcher Qi-HuaWang.
Keywords
Semi-Linear Partial Linear Regression Model, The Parameter Regression Model, The Non-Parametric Regression Model, Incomplete Data.Metrics