Abstract
In this chapter, we will provide an overview of the current status of research involving Bayesian inference in wavelet nonparametric problems. In many statistical applications, there is a need for procedures to (i) adapt to data and (ii) use prior information. The interface of wavelets and the Bayesian paradigm provide a natural terrain for both of these goals.
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Vidakovic, B. (1998). Wavelet-Based Nonparametric Bayes Methods. In: Dey, D., Müller, P., Sinha, D. (eds) Practical Nonparametric and Semiparametric Bayesian Statistics. Lecture Notes in Statistics, vol 133. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1732-9_7
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DOI: https://doi.org/10.1007/978-1-4612-1732-9_7
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