Estimation of Regression Coefficients Through Compound Geometric Lagmodel Using Data Mining

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 dist...

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Bibliographic Details
Published inBulletin of pure & applied sciences. Sec. E, Mathematics & statistics Vol. 35e; no. 1; pp. 1 - 12
Main Authors Raghavaiah, A.V.S, Akhtar, P. Mohammed
Format Journal Article
LanguageEnglish
Published BPAS Research 01.01.2016
Subjects
and Goodness of fit
Cause and Effect
Data mining
Durbin-Watson Test
Error sum of squares
Explanatory variables
Linear regression model
Missing values
Parameters
Random disturbances
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Summary: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.
ISSN:0970-6577
2320-3226
DOI:10.5958/2320-3226.2016.00001.1