Asymptotic distribution of the least squares estimator in the first-order autoregressive process
| dc.creator | Gonen, Mithat | |
| dc.date.accessioned | 2016-11-14T23:13:33Z | |
| dc.date.available | 2011-02-18T19:35:29Z | |
| dc.date.available | 2016-11-14T23:13:33Z | |
| dc.date.issued | 1996-08 | |
| dc.degree.department | Statistics | en_US |
| dc.description.abstract | This study is about the asymptotic distribution of the least squares estimator in nonstationary first-order autoregressive processes. These processes are commonly used to model economic time series and the desired distribution is important in finding the size of the so-called unit root tests. Our approach is based on the asymptotic characterization of the distribution in terms of a functional of the standard Wiener process. We use the Karhunen- Loeve expansion for the Wiener process and obtain the solution using characteristic functions and the Fourier inversion theorem. As compared to the previous studies, our method provides a conceptually simple framework in which one can investigate more complicated models. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/2346/11306 | en_US |
| dc.language.iso | eng | |
| dc.publisher | Texas Tech University | en_US |
| dc.rights.availability | Unrestricted. | |
| dc.subject | Autoregression (Statistics) | en_US |
| dc.subject | Least squares | en_US |
| dc.subject | Asymptotic distribution (Probability theory) | en_US |
| dc.title | Asymptotic distribution of the least squares estimator in the first-order autoregressive process | |
| dc.type | Thesis |