A Memoir on Model Selection Criterion between Two Nested and Non-Nested Stochastic Linear Regression Models
DOI:
https://doi.org/10.14419/ijet.v7i4.10.21219Keywords:
Test statistic, OLS residual sum of squares, nested and non-nested stochastic linear regression model, internally studentized residuals, OLS estimator.Abstract
The main purpose of this paper is to discuss some applications of internally studentized residuals 9n the model selection criterion between two nested and non-nested stochastic linear regression models. Joseph et.al [1] formulated various proposals from a Bayesian decision-theoretic perspective regarding model selection Criterion. Oliver Francois et.al [2] proposed novel approaches to model selection based on predictive distributions and approximations of the deviance. Jerzy szroeter [3] in his paper depicted the development of statistical methods to test non-nested models including regressions, simultaneous equations. In particular new criteria for a model selection between two nested/ non-nested stochastic linear regression models have been suggested here.
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Received date: October 7, 2018
Accepted date: October 7, 2018
Published date: October 2, 2018