A0280
Title: Oversampling of stochastic processes
Authors: Stephen Pollock - University of Leicester (United Kingdom) [presenting]
Abstract: Discrete-time ARMA processes can be placed in a one-to-one correspondence with a set of continuous-time processes that are bounded in frequency by the Nyquist value of $\pi$ radians per sample period. It is well known that, if data are sampled from a continuous process of which the maximum frequency exceeds the Nyquist value, then there will be a problem of aliasing. However, if the sampling is too rapid, then other problems will arise that will cause the ARMA estimates to be severely biased.The nature of these problems are revealed and it is shown how they may be overcome.
