Efficiency in estimation of memory |
| |
Authors: | Willa W. Chen |
| |
Affiliation: | Department of Statistics, Texas A&M University, College Station, TX 77843-3143, USA |
| |
Abstract: | We study the efficiency of semiparametric estimates of memory parameter. We propose a class of shift invariant tapers of order (p,q). For a fixed p, the variance inflation factor of the new tapers approaches 1 as q goes to infinity. We show that for d∈(−1/2,p+1/2), the proposed tapered Gaussian semiparametric estimator has the same limiting distribution as the nontapered version for d∈(−1/2,1/2). The new estimator is mean and polynomial trend invariant, and is computationally advantageous in comparison to the recently proposed exact local Whittle estimator. The simulation study shows that our estimator has comparable or better mean squared error in finite samples for a variety of models. |
| |
Keywords: | Gaussian semiparametric estimation Tapering Periodogram |
本文献已被 ScienceDirect 等数据库收录! |
|