Package: robfilter
Version: 4.1.2
Date: 2019-11-17
Title: Robust Time Series Filters
Authors@R: c(person("Roland", "Fried", 
                    email = "fried@statistik.tu-dortmund.de", 
                    role = c("aut", "cre")),
             person("Karen", "Schettlinger", 
                    email = "schettlinger@statistik.tu-dortmund.de",
                    role = "aut"),
             person("Matthias", "Borowski",
                    email = "borowski@statistik.tu-dortmund.de",
                    role = "aut"),
             person("Robin", "Nunkesser", 
                    role = "ctb"),
             person("Thorsten", "Bernholt",
                    role = "ctb"))
Author: Roland Fried [aut, cre],
  Karen Schettlinger [aut],
  Matthias Borowski [aut],
  Robin Nunkesser [ctb],
  Thorsten Bernholt [ctb]
Maintainer: Roland Fried <fried@statistik.tu-dortmund.de>
Imports: stats, graphics, utils
Depends: R (>= 3.6.0), robustbase, MASS, lattice
Description: 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>.
License: GPL (>= 2)
URL: http://www.statistik.tu-dortmund.de/fried.html
LazyData: yes
Repository: CRAN
NeedsCompilation: yes
SystemRequirements: C++11
Packaged: 2019-11-17 11:13:58 UTC; abbas
Date/Publication: 2019-11-21 14:00:02 UTC
Built: R 4.0.2; x86_64-w64-mingw32; 2020-08-02 07:30:38 UTC; windows
Archs: i386, x64
