Package: mrbsizeR
Type: Package
Title: Scale Space Multiresolution Analysis of Random Signals
Version: 1.2.1.1
Date: 2019-12-10
Authors@R: c(
    person("Thimo", "Schuster", email = "thimo.schuster@gmail.com", role = c("aut")),
    person("Roman", "Flury", email = "roman.flury@math.uzh.ch", role = c("cre", "aut")),
    person("Leena", "Pasanen", email = "leena.pasanen@oulu.fi", role = "ctb"),
    person("Reinhard", "Furrer", email = "reinhard.furrer@math.uzh.ch", role = "ctb"))
Maintainer: Roman Flury <roman.flury@math.uzh.ch>
Description: 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>.
    Matlab code is available under <http://cc.oulu.fi/~lpasanen/MRBSiZer/>.
License: GPL-2
LazyData: TRUE
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
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
BugReports: https://github.com/romanflury/mrbsizeR/issues
URL: https://github.com/romanflury/mrbsizeR,
        https://romanflury.github.io/mrbsizeR/
NeedsCompilation: yes
Packaged: 2020-03-30 12:10:57 UTC; hornik
Author: Thimo Schuster [aut],
  Roman Flury [cre, aut],
  Leena Pasanen [ctb],
  Reinhard Furrer [ctb]
Repository: CRAN
Date/Publication: 2020-04-01 11:25:03 UTC
Built: R 4.1.3; x86_64-w64-mingw32; 2023-04-17 19:00:34 UTC; windows
Archs: i386, x64
