haarfisz-package {haarfisz}

A Haar-Fisz Algorithm for Poisson Intensity Estimation.

Description

Package to denoise Poisson distributed sequence where underlying intensity is not constant. Uses the multiscale variance-stabilization method called the Haar-Fisz transform. Contains functions to carry out the foward and inverse Haar-Fisz transform and denoising on near-Gaussian sequences. Can also carry out cycle-spinning.

Details

Package to denoise Poisson distributed sequence where underlying intensity is not constant. Uses the multiscale variance-stabilization method called the Haar-Fisz transform. Contains functions to carry out the foward and inverse Haar-Fisz transform and denoising on near-Gaussian sequences. Can also carry out cycle-spinning. See main routine denoise.poisson

Author(s)

Piotr Fryzlewicz>

References

Fryzlewicz, P. (2003) Wavelet Techniques for Time Series and Poisson Data. PhD Thesis, University of Bristol, Bristol, UK https://www.ma.imperial.ac.uk/~gnason/Research/MAPZFthesis.ps.gz

Fryzlewicz, P. and Nason, G.P. (2004) A Haar-Fisz algorithm for Poisson intensity estimation. Journal of Computational and Graphical Statistics, 13, 621-638. doi:10.1198/106186004X2697

Nason, G.P. (2008) Wavelet Methods in Statistics with R. Springer: New York (Section 6.4) doi:10.1007/978-0-387-75961-6

See Also

denoise.poisson, hft, hft.inv

Examples

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# Main Poisson denoising function is denoise.poisson
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# Forward Haar-Fisz transform is hft
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# Inverse Haar-Fisz transform is hft.inv