A0307
Title: Robust spectral estimators for long-memory processes
Authors: Valderio Anselmo Reisen - DEST-CCE-UFES (Brazil) [presenting]
Abstract: The outlier effects on the estimation of a spectral estimator is discussed for long memory process under additive outliers and robust spectral estimators are proposed. Some asymptotic properties of the proposed robust methods are derived and Monte Carlo simulations investigate their empirical properties. Pollution series, such as PM (Particulate matter), SO2 (Sulfur dioxide), are the examples investigated to show the usefulness of the robust methods in real applications. These pollutants present, in general, observations with high levels of pollutant concentrations which may produce sample densities with heavy tails and these high levels can be identified as outliers which can destroy the statistical properties of sample functions such as the standard mean, covariance and periodogram.
