Package: mrbsizeR 1.2.1

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>. Matlab code is available under <http://cc.oulu.fi/~lpasanen/MRBSiZer/>.

Authors:Thimo Schuster [aut], Roman Flury [cre, aut], Leena Pasanen [ctb], Reinhard Furrer [ctb]

mrbsizeR_1.2.1.tar.gz
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mrbsizeR.pdf |mrbsizeR.html✨
mrbsizeR/json (API)
NEWS

# Install 'mrbsizeR' in R:
install.packages('mrbsizeR', repos = c('https://romanflury.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/romanflury/mrbsizer/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

4.22 score 1 stars 33 scripts 202 downloads 15 exports 6 dependencies

Last updated 5 years agofrom:936edff8a3. Checks:OK: 4 NOTE: 5. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-win-x86_64NOTENov 02 2024
R-4.5-linux-x86_64NOTENov 02 2024
R-4.4-win-x86_64NOTENov 02 2024
R-4.4-mac-x86_64NOTENov 02 2024
R-4.4-mac-aarch64NOTENov 02 2024
R-4.3-win-x86_64OKNov 02 2024
R-4.3-mac-x86_64OKNov 02 2024
R-4.3-mac-aarch64OKNov 02 2024

Exports:CImapdctMatrixdftMatrixeigenLaplaceeigenQspherefftshiftHPWmapifftshiftMinLambdamrbsizeRgridmrbsizeRspherermvtDCTTaperingPlottridiagturnmat

Dependencies:dotCall64fieldsmapsRcppspamviridisLite

mrbsizeR: Scale space multiresolution analysis in R

Thimo Schuster, Roman Flury

Rendered frommrbsizeR.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2019-12-06
Started: 2018-05-07

Readme and manuals

Help Manual

Help pageTopics
A short title line describing what the package doesmrbsizer-package mrbsizer
Computation of simultaneous credible intervals.CImap
Create a n-by-n discrete cosine transform matrix.dctMatrix
Create a n-by-n discrete Fourier transform matrix.dftMatrix
Generate eigenvalues of discrete Laplace matrix.eigenLaplace
Generate eigenvalues of precision matrix Q on the surface of a sphere.eigenQsphere
Swap the quadrants or halves of a 2d matrix.fftshift
Computation of pointwise and highest pointwise probabilities.HPWmap
Inverse FFT shift of a 2d matrix.ifftshift
Numerical optimization for finding appropriate smoothing levels.MinLambda
mrbsizeR: Scale space multiresolution analysis in R.mrbsizeR-package mrbsizeR
Multiresolution analysis of random signals.mrbsizeRgrid
Multiresolution analysis of random signals for spherical data.mrbsizeRsphere
Plot of simultaneous credible intervals.plot.CImapGrid
Plotting of simultaneous credible intervals on a sphere.plot.CImapSphere
Plotting of pointwise and highest pointwise probabilities.plot.HPWmapGrid
Plotting of pointwise and highest pointwise probabilities on a sphere.plot.HPWmapSphere
Plot of objective function for finding appropriate smoothing parameters.plot.minLambda
Plotting of scale-dependent features.plot.smMeanGrid
Plotting of scale-dependent features on a sphere.plot.smMeanSphere
Sampling from marginal posterior multivariate t-distribution.rmvtDCT
Plot of tapering functions.TaperingPlot
Generate a tridiagonal matrix.tridiag
Turn matrix 90 degrees counter-clockwise.turnmat