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.
- Version1.3
- R versionunknown
- LicenseGPL-2
- Needs compilation?Yes
- Last release02/14/2024
Documentation
Team
Roman Flury
MaintainerShow author detailsReinhard Furrer
Thimo Schuster
Show author detailsRolesAuthorLeena Pasanen
Show author detailsRolesContributor
Insights
Last 30 days
This package has been downloaded 221 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 2 times.
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Last 365 days
This package has been downloaded 2,718 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 37 downloads.
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Dependencies
- Depends1 package
- Imports2 packages
- Suggests3 packages
- Linking To1 package
- Reverse Suggests1 package