Testing serial correlation for partially nonlinear models

Partially nonlinear models as extensions of partially linear models are extensively used in statistical modeling This paper considers the spline empirical log-likelihood ratio for testing serial correlation in partially nonlinear models It is shown that the proposed empirical log-likelihood ratio converges to the standard chi-square distribution under the null hypothesis of no serial correlation Some simulations are conducted to estimate the rejection probabilities under the null hypothesis and serial correlation An example of application is also illustrated (C) 2009 The Korean Statistical Society Published by Elsevier B V All rights reserved