robscale: Faster Robustness: Accelerated Estimation of Location and Scale
Robust estimation ensures statistical reliability in data
contaminated by outliers. Yet, computational bottlenecks in existing 'R'
implementations frequently obstruct both very small sample analysis and
large-scale processing. 'robscale' resolves these inefficiencies by
providing high-performance implementations of logistic M-estimators
and the 'Qn' and 'Sn' scale estimators. By leveraging platform-specific Single
Instruction, Multiple Data (SIMD) vectorization and Intel Threading
Building Blocks (TBB) parallelism, the package delivers speedups of
11–39x for small samples and up to 10x for massive datasets. These
performance gains enable the integration of robust statistics into modern,
time-critical computational workflows. Replaces 'revss' with an 'Rcpp'
backend.
| Version: |
0.1.5 |
| Imports: |
Rcpp (≥ 1.0.0), RcppParallel (≥ 5.0.0) |
| LinkingTo: |
Rcpp, RcppParallel, BH |
| Suggests: |
testthat (≥ 3.0.0), revss, microbenchmark, robustbase |
| Published: |
2026-03-09 |
| DOI: |
10.32614/CRAN.package.robscale |
| Author: |
Dennis Alexis Valin Dittrich
 [aut, cre,
cph] |
| Maintainer: |
Dennis Alexis Valin Dittrich <davd at economicscience.net> |
| BugReports: |
https://github.com/davdittrich/robscale/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/davdittrich/robscale,
https://doi.org/10.5281/zenodo.18828607 |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make, TBB |
| Citation: |
robscale citation info |
| Materials: |
NEWS |
| CRAN checks: |
robscale results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=robscale
to link to this page.