Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5096737 | Journal of Econometrics | 2009 | 12 Pages |
Abstract
The time varying empirical spectral measure plays a major role in the treatment of inference problems for locally stationary processes. The properties of the empirical spectral measure and related statistics are studied - both when its index function is fixed or when dependent on the sample size. In particular we prove a general central limit theorem. Several applications and examples are given including semiparametric Whittle estimation, local least squares estimation and spectral density estimation.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Rainer Dahlhaus,