2022, Vol. 3, Issue 2, Part B
Model specification test against non-nested univariate and multivariate nonlinear regression models
Author(s): Dr. Kesavulu Poola, V Pavankumari, J Anil Kumar and M Bhupathi Naidu
Abstract: In an econometric model, Non-nested hypothesis tests give the best path to test the specification of univariate and multivariate Regression models. The model introduced by Cox for evaluate different set of hypotheses was used to the alternative between two non-nested linear regression models. This paper examines the current literature on non-nested univariate and multivariate hypothesis testing in the context of nonlinear regression and related models. The paper also covered testing the hypothesis for non-nested univariate and multivariate nonlinear regression models. The principal part of the article derives the results and explains that they are identifiable as generalizations of the univariate-equation case. It is also revealed that the computation of the test statistic involves very little calculation beyond that necessary to estimate the models.
Pages: 130-133 | Views: 295 | Downloads: 116
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How to cite this article:
Dr. Kesavulu Poola, V Pavankumari, J Anil Kumar and M Bhupathi Naidu. Model specification test against non-nested univariate and multivariate nonlinear regression models. Journal of Mathematical Problems, Equations and Statistics. 2022; 3(2): 130-133.