Likelihoods for Signal Plus “White Noise” Versus “White Noise”

Antonio F. Gualtierotti
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Antonio F. Gualtierotti: University of Lausanne, HEC and IDHEAP

Chapter Chapter 13 in Detection of Random Signals in Dependent Gaussian Noise, 2015, pp 927-960 from Springer

Abstract: Abstract In this chapter, one obtains the likelihood for a “signal plus noise” model for which the noise is a Cramér-Hida process. The “white noise” of the chapter’s title is a convenience: for a short glimpse at “real white noise,” one may, for example, look at [164, p. 260]. As for the finite dimensional case, the road to the likelihood is based on a version of Girsanov’s theorem, and the likelihood itself follows when the “signal plus noise,” that is, the observation process, has a representation as the solution of a stochastic differential equation.

Keywords: White Noise; Probability Space; Integrable Function; Stochastic Differential Equation; Moment Condition (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-22315-5_13

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DOI: 10.1007/978-3-319-22315-5_13

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