const.Q

<p>Correction factors for the regression-free Q scale estimator (Rousseeuw and Hubert, 1996, Gelper et al., 2009) to achieve unbiasedness under Gaussian noise; required by the function <code>scarm.filter</code>.</p>

datasets

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>.

Roland Fried

robfilter

Robust Time Series Filters

Karen Schettlinger

Matthias Borowski

Robin Nunkesser

Thorsten Bernholt

const.Q function

<p>The format is:
 num [1:151] NA NA NA NA 2.17 ...</p>

Format

Correction factors to achieve unbiasedness of the regression-free Q scale estimator — const.Q

Correction factors to achieve unbiasedness of the regression-free Q scale estimator

const.Q: Correction factors to achieve unbiasedness of the regression-free Q scale estimator

Description

Usage

Arguments

Format

References