Name
Abstract | ||
|---|---|---|
In this paper, we consider the application of the empirical likelihood method to the generalized random coefficient autoregressive (GRCA) model. The empirical log-likelihood ratio statistics are proposed and the nonparametric versions of the Wilk’s theorem are obtained. Furthermore, when the order of the model is 1, we also derive a test statistic to test the stationary–ergodicity based on the conditional least-squares method. Numerical results from simulation studies suggest that the empirical likelihood method is more accurate than the normal approximation-based method of Hwang and Basawa (1998) [1]. Some simulation studies are also conducted to investigate the finite sample performances of the proposed test. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.mcm.2011.12.002 | Mathematical and Computer Modelling |
Keywords | Field | DocType |
Empirical likelihood,Least squares estimation,Asymptotic normality,Generalized random coefficient autoregressive model,Confidence region | Autoregressive model,Score test,Mathematical optimization,Test statistic,Likelihood-ratio test,Empirical likelihood,Nonparametric statistics,Statistical inference,STAR model,Statistics,Mathematics | Journal |
Volume | Issue | ISSN |
56 | 7 | 0895-7177 |
Citations | PageRank | References |
2 | 0.80 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiwen Zhao | 1 | 25 | 5.23 |
| yang | 2 | 15 | 7.73 |