Statistics Seminars: Hurst exponent estimation for long-memory processes using wavelet lifting
10 February 2014 14:00 in CM221
Reliable estimation of long-range dependence (LRD) parameters, such as the Hurst exponent, is a well studied problem in the statistical literature. However, when the observed time series presents missingness or is naturally irregularly sampled, the current literature is sparse with most approaches requiring heavy modifications. In this talk I shall present a technique for estimating the Hurst exponent of an LRD time series that naturally deals with the time domain irregularity. The method is based on a flexible wavelet transform built by means of the lifting scheme, and we shall demonstrate its performance.
Contact firstname.lastname@example.org for more information