mrbsizeR: Scale Space Multiresolution Analysis of Random Signals

A method for the multiresolution analysis of spatial fields and images to capture scale-dependent features. mrbsizeR is based on scale space smoothing and uses differences of smooths at neighbouring scales for finding features on different scales. To infer which of the captured features are credible, Bayesian analysis is used. The scale space multiresolution analysis has three steps: (1) Bayesian signal reconstruction. (2) Using differences of smooths, scale-dependent features of the reconstructed signal can be found. (3) Posterior credibility analysis of the differences of smooths created. The method has first been proposed by Holmstrom, Pasanen, Furrer, Sain (2011) <doi:10.1016/j.csda.2011.04.011> and extended in Flury, Gerber, Schmid and Furrer (2021) <doi:10.1016/j.spasta.2020.100483>.

Version: 1.3
Depends: R (≥ 3.0.0), maps (≥ 3.1.1)
Imports: fields (≥ 8.10), stats (≥ 3.0.0), grDevices (≥ 3.0.0), graphics (≥ 3.0.0), methods (≥ 3.0.0), Rcpp (≥ 0.12.14)
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, testthat
Published: 2024-02-14
DOI: 10.32614/CRAN.package.mrbsizeR
Author: Thimo Schuster [aut], Roman Flury [cre, aut], Leena Pasanen [ctb], Reinhard Furrer [ctb]
Maintainer: Roman Flury <roman.flury at>
License: GPL-2
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: mrbsizeR results


Reference manual: mrbsizeR.pdf
Vignettes: 'mrbsizeR': Scale space multiresolution analysis in R


Package source: mrbsizeR_1.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): mrbsizeR_1.3.tgz, r-oldrel (arm64): mrbsizeR_1.3.tgz, r-release (x86_64): mrbsizeR_1.3.tgz, r-oldrel (x86_64): mrbsizeR_1.3.tgz
Old sources: mrbsizeR archive

Reverse dependencies:

Reverse suggests: specklestar


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