Multiscale Poisson data smoothing

@inproceedings{Jansen2006MultiscalePD,
  title={Multiscale Poisson data smoothing},
  author={Maarten Jansen and TU Eindhoven},
  year={2006}
}
This paper introduces a framework for nonlinear, multiscale decompositions of Poisson data with piecewise smooth intensity curves. The key concept is conditioning on the sum of the observations that are involved in the computation of a given coefficient. Within this framework, most classical wavelet thresholding schemes for data with additive, homoscedastic noise apply. Any family of wavelet transforms (orthogonal, biorthogonal, second generation) can be incorporated into this framework. The… CONTINUE READING
Highly Cited
This paper has 59 citations. REVIEW CITATIONS
36 Citations
34 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 36 extracted citations

60 Citations

0510'06'09'12'15'18
Citations per Year
Semantic Scholar estimates that this publication has 60 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 34 references

A wavelet-Fisz algorithm for Poisson intensity estimation

  • P. Fryźlewicz, G. Nason
  • Journal of Computational and Graphical Statistics
  • 2003
Highly Influential
12 Excerpts

Bayesian multiscale models for Poisson processes

  • E. D. Kolaczyk
  • J. Amer. Statist. Assoc.,
  • 1999
Highly Influential
13 Excerpts

A gaussian cubature formula for the computation of generalized b-splines and its application to serial correlation

  • V. K. Kaishev
  • In Statistical multiple integration (Arcata, CA,
  • 1991
Highly Influential
5 Excerpts

Wavelet shrinkage for natural exponential families with cubicariance functions

  • A. Antoniadis, P. Besbeas, T. Sapatinas
  • Sankhya, Series A,
  • 2001
Highly Influential
5 Excerpts

Wavelet shrinkage for natural exponential families with quadratic variance functions

  • A. Antoniadis, T. Sapatinas
  • Biometrika
  • 2001
Highly Influential
6 Excerpts

Non-linear wavelet methods for recovery of signals, densities and spectra from indirect and noisy data

  • D. L. Donoho
  • Different perspectives on wavelets,
  • 1993
Highly Influential
5 Excerpts

The transformation of Poisson, binomial and negative binomial data

  • F. Anscombe
  • Biometrika
  • 1948
Highly Influential
5 Excerpts

Similar Papers

Loading similar papers…