Gaussian estimation of parametric spectral density with unknown pole
Giraitis, L. ; Hidalgo, J. ; Robinson, P. M.
Ann. Statist., Tome 29 (2001) no. 2, p. 987-1023 / Harvested from Project Euclid
We consider a parametric spectral density with power-law behavior about a fractional pole at the unknown frequency $\omega$. The case of known $\omega$, especially $\omega =0$, is standard in the long memory literature. When $omega$ is unknown, asymptotic distribution theory for estimates of parameters, including the (long) memory parameter, is significantly harder. We study a form of Gaussian estimate. We establish $n$-consistency of the estimate of $\omega$, and discuss its (non-standard) limiting distributional behavior. For the remaining parameter estimates,we establish $\sqrt{n}$-consistency and asymptotic normality.
Publié le : 2001-08-14
Classification:  Long range dependence,  unknown pole,  62M10,  60G18
@article{1013699989,
     author = {Giraitis, L. and Hidalgo, J. and Robinson, P. M.},
     title = {Gaussian estimation of parametric spectral density with unknown
			 pole},
     journal = {Ann. Statist.},
     volume = {29},
     number = {2},
     year = {2001},
     pages = { 987-1023},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1013699989}
}
Giraitis, L.; Hidalgo, J.; Robinson, P. M. Gaussian estimation of parametric spectral density with unknown
			 pole. Ann. Statist., Tome 29 (2001) no. 2, pp.  987-1023. http://gdmltest.u-ga.fr/item/1013699989/