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Multiscale variance stabilization via maximum likelihood

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  • G. P. Nason

Abstract

This article proposes maximum likelihood approaches for multiscale variance stabilization transformations for independently and identically distributed data. For two multiscale variance stabilization transformations we present new unified theoretical results on their Jacobians, a key component of the likelihood. The results provide a deeper understanding of the transformations and the ability to compute the likelihood in linear time. The transformations are shown empirically to compare favourably to the Box–Cox transformation.

Suggested Citation

  • G. P. Nason, 2014. "Multiscale variance stabilization via maximum likelihood," Biometrika, Biometrika Trust, vol. 101(2), pages 499-504.
    • Handle: RePEc:oup:biomet:v:101:y:2014:i:2:p:499-504.
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    File URL: http://hdl.handle.net/10.1093/biomet/ast072
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    Cited by:

    1. Antonis A. Michis & Guy P. Nason, 2017. "Case study: shipping trend estimation and prediction via multiscale variance stabilisation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(15), pages 2672-2684, November.

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