Inference In Nonlinear Regression Model With Heteroscedastic Errors

B. Mahaboob; Dr. M. Ramesh; Dr. Sk. Khadar Babu; P. Srivyshnavi; Prof. P. B.Sireesha; Balasiddamuni

Volume : V, Issue : V, May - 2016

Inference In Nonlinear Regression Model With Heteroscedastic Errors

B. Mahaboob, Dr. M. Ramesh, Dr. Sk. Khadar Babu, P. Srivyshnavi, Prof. P. B. Sireesha, Balasiddamuni

Abstract :

An advent of modern computer science has made it possible for the applied mathematician to study the inferential aspects of an increasing number of nonlinear regression models in recent years. The inferential aspects for nonlinear regression models and the error assumptions are usually analogous to those made for linear regression models. The tests for the hypotheses on parameters of nonlinear regression models are usually based on nonlinear least squares estimates and the normal assumptions of error variables. A more common problem with data that are best fit by a nonlinear regression model than with data that can be adequately fit by the linear regression model is the problem of heteroscedasticity of errors. The problem of heteroscedasticity can be studied with reference to nonlinear regression models in a variety of ways. In the present study, an attempt has been made by developing inferential method for heteroscedastic nonlinear regression model.