Package: robfilter 4.1.5

Roland Fried

robfilter: Robust Time Series Filters

Implementations for several robust procedures that allow for (online) extraction of the signal of univariate or multivariate time series by applying robust regression techniques to a moving time window are provided. Included are univariate filtering procedures based on repeated-median regression as well as hybrid and trimmed filters derived from it; see Schettlinger et al. (2006) <doi:10.1515/BMT.2006.010>. The adaptive online repeated median by Schettlinger et al. (2010) <doi:10.1002/acs.1105> and the slope comparing adaptive repeated median by Borowski and Fried (2013) <doi:10.1007/s11222-013-9391-7> choose the width of the moving time window adaptively. Multivariate versions are also provided; see Borowski et al. (2009) <doi:10.1080/03610910802514972> for a multivariate online adaptive repeated median and Borowski (2012) <doi:10.17877/DE290R-14393> for a multivariate slope comparing adaptive repeated median. Furthermore, a repeated-median based filter with automatic outlier replacement and shift detection is provided; see Fried (2004) <doi:10.1080/10485250410001656444>.

Authors:Roland Fried [aut, cre], Karen Schettlinger [aut], Matthias Borowski [aut], Robin Nunkesser [ctb], Thorsten Bernholt [ctb]

robfilter_4.1.5.tar.gz
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robfilter_4.1.5.tgz(r-4.4-emscripten)robfilter_4.1.5.tgz(r-4.3-emscripten)
robfilter.pdf |robfilter.html✨
robfilter/json (API)

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

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • const - Correction factors to achieve unbiasedness of the Qn scale estimator
  • const.Q - Correction factors to achieve unbiasedness of the regression-free Q scale estimator
  • critvals - Critical Values for the RM Goodness of Fit Test
  • dfs - Degrees of freedom for the SCARM test statistic.
  • multi.ts - Generated Multivariate Time Series
  • sizecorrection - Bias correction factors for the robust scale estimators MAD, Sn, Qn, and LSH
  • timecorrection - Correction factors for the scale estimation of the filtering procedure proposed by Fried (2004).
  • var.n - Variance of the Repeated Median slope estimator.

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

16 exports 2 stars 1.45 score 4 dependencies 4 mentions 42 scripts 663 downloads

Last updated 2 months agofrom:8ea203538d. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 15 2024
R-4.5-linux-x86_64OKSep 15 2024

Exports:adore.filterdr.filterdw.filterhybrid.filterlms.filterlqd.filterlts.filtermadore.filtermed.filtermscarm.filterrm.filterrobreg.filterrobust.filterscarm.filterwrm.filterwrm.smooth

Dependencies:DEoptimRlatticeMASSrobustbase

Readme and manuals

Help Manual

Help pageTopics
Robust Time Series Filtersrobfilter-package robfilter
A Robust Adaptive Online Repeated Median Filter for Univariate Time Seriesadore.filter
Correction factors to achieve unbiasedness of the Qn scale estimatorconst
Correction factors to achieve unbiasedness of the regression-free Q scale estimatorconst.Q
Critical Values for the RM Goodness of Fit Testcritvals
Degrees of freedom for the SCARM test statistic.dfs
Deepest Regression (DR) filterdr.filter
Robust Double Window Filtering Methods for Univariate Time Seriesdw.filter dw.filter.online
Robust Hybrid Filtering Methods for Univariate Time Serieshybrid.filter
Least Median of Squares (LMS) filterlms.filter
Least Quartile Difference filterlqd.filter
Least Trimmed Squares (LTS) filterlts.filter
A multivariate adaptive online repeated median filtermadore.filter
Median (MED) filtermed.filter
MSCARM (Multivariate Slope Comparing Adaptive Repeated Median)mscarm.filter
Generated Multivariate Time Seriesmulti.ts
Repeated Median (RM) filterrm.filter
Robust Regression Filters for Univariate Time Seriesrobreg.filter
Robust Filtering Methods for Univariate Time Seriesrobust.filter
SCARM (Slope Comparing Adaptive Repeated Median)scarm.filter
Bias correction factors for the robust scale estimators MAD, Sn, Qn, and LSHsizecorrection
Correction factors for the scale estimation of the filtering procedure proposed by Fried (2004).timecorrection
Variance of the Repeated Median slope estimator.var.n
Weighted Repeated Median Filters for Univariate Time Serieswrm.filter
Weighted Repeated Median Smoothingwrm.smooth