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Oversampling of stochastic processes

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  • D.S.G. Pollock

    ()
    (University of Leicester)

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 ð 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 paper reveals the nature of these problems and it shows how they may be overcome.

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Bibliographic Info

Paper provided by Department of Applied Econometrics, Warsaw School of Economics in its series Working Papers with number 44.

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Length: 18 pages
Date of creation: 25 May 2010
Date of revision:
Handle: RePEc:wse:wpaper:44

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Related research

Keywords: Stochastic Differential Equations; Band-Limited Stochastic Processes; Oversampling;

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  1. Tommaso Proietti, 2007. "Band Spectral Estimation for Signal Extraction," CEIS Research Paper 104, Tor Vergata University, CEIS.
  2. Adrian Pagan, 1997. "Towards an Understanding of Some Business Cycle Characteristics," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 30(1), pages 1-15.
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