Publication: The block criterion for multiscale inference about a density, with applications to other multiscale problems
The block criterion for multiscale inference about a density, with applications to other multiscale problems
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Rufibach, K., & Walther, G. (2010). The block criterion for multiscale inference about a density, with applications to other multiscale problems. Journal of Computational and Graphical Statistics, 19(1), 175–190. https://doi.org/10.1198/jcgs.2009.07071
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The use of multiscale statistics, i.e. the simultaneous inference about various stretches of data via multiple localized statistics, is a natural and popular method for inference about e.g. local qualitative characteristics of a regression function, a density, or its hazard rate. We focus on the problem of providing simultaneous confidence statements for the existence of local increases and decreases of a density and address several statistical and computational issues concerning such multiscale statistics. We first review the benefit
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- Rufibach, K
- Walther, G
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Rufibach, K., & Walther, G. (2010). The block criterion for multiscale inference about a density, with applications to other multiscale problems. Journal of Computational and Graphical Statistics, 19(1), 175–190. https://doi.org/10.1198/jcgs.2009.07071
