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LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R

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  • Eckley, Idris A.
  • Nason, Guy P.

Abstract

Locally stationary process representations have recently been proposed and applied to both time series and image analysis applications. This article describes an implementation of the locally stationary two-dimensional wavelet process approach in R. This package permits construction of estimates of spatially localized spectra and localized autocovariance which can be used to characterize structure within images.

Suggested Citation

  • Eckley, Idris A. & Nason, Guy P., 2011. "LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i03).
    • Handle: RePEc:jss:jstsof:v:043:i03
    DOI: http://hdl.handle.net/10.18637/jss.v043.i03
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    References listed on IDEAS

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    1. Sébastien Van Bellegem & Rainer Dahlhaus, 2006. "Semiparametric estimation by model selection for locally stationary processes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(5), pages 721-746, November.
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