Bernoulli

Counting process intensity estimation by orthogonal wavelet methods

Prakash N. Patil and Andrew T.A. Wood

Full-text: Open access

Abstract

In recent years wavelet-based methods have been proposed to estimate density and regression functions, most often in settings with independent and identically distributed observations. An attractive feature of these methods is that the rate of convergence is unaffected by the presence of discontinuities in the function being estimated. We provide structure and mean-square analyses of wavelet-based estimators of counting process intensities in the context of the multiplicative intensity model.

Article information

Source
Bernoulli, Volume 10, Number 1 (2004), 1-24.

Dates
First available in Project Euclid: 23 February 2004

Permanent link to this document
https://projecteuclid.org/euclid.bj/1077544601

Digital Object Identifier
doi:10.3150/bj/1077544601

Mathematical Reviews number (MathSciNet)
MR2044591

Zentralblatt MATH identifier
1040.62075

Keywords
counting process mean integrated square error multiplicative intensity model smoothness wavelet thresholding

Citation

Patil, Prakash N.; Wood, Andrew T.A. Counting process intensity estimation by orthogonal wavelet methods. Bernoulli 10 (2004), no. 1, 1--24. doi:10.3150/bj/1077544601. https://projecteuclid.org/euclid.bj/1077544601


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