Bulletin of Pure & Applied Sciences- Mathematics and Statistics
  • Year: 2016
  • Volume: 35e
  • Issue: 1

Estimation of Regression Coefficients Through Compound Geometric Lagmodel Using Data Mining

1Lecturer in, Statistics, SKSC Degree College (affiliated to Y V University), Proddatur, Kadapa (Dist) Mail id: avsraghavaiah61@gamil.com

2Professor, Department of Statistics, S.K University, Anantapuramu, Mail id: palagiriakhtar@rediffmail.com

Online published on 28 June, 2016.

Abstract

Econometrics deals with the measurement of economic relationships. It may be considered as the integration of mathematics, economics and statistics for the purpose of providing estimation for the parameters of the economic relationships. Econometric methods designed to take an account of random disturbances or errors. The disturbances can be estimated by using different types of estimation procedures. In the present study an inferential aspects of linear regression model is considered, and it is fitted with an agricultural data, which was collected from a data mining. The fitted model was tested its goodness of fit by using Durbin-Watson test and estimated the error sum of squares.

Keywords

Parameters, Random disturbances, Linear regression model, Missing values, Data mining, and Goodness of fit, Explanatory variables, Cause and Effect, Durbin-Watson Test, Error sum of squares