Exponential smoothing based on L-estimation

Přemysl Bejda; Tomáš Cipra

Kybernetika (2015)

  • Volume: 51, Issue: 6, page 973-993
  • ISSN: 0023-5954

Abstract

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Robust methods similar to exponential smoothing are suggested in this paper. First previous results for exponential smoothing in L 1 are generalized using the regression quantiles, including a generalization to more parameters. Then a method based on the classical sign test is introduced that should deal not only with outliers but also with level shifts, including a detection of change points. Properties of various approaches are investigated by means of a simulation study. A real data example is used as an illustration.

How to cite

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Bejda, Přemysl, and Cipra, Tomáš. "Exponential smoothing based on L-estimation." Kybernetika 51.6 (2015): 973-993. <http://eudml.org/doc/276221>.

@article{Bejda2015,
abstract = {Robust methods similar to exponential smoothing are suggested in this paper. First previous results for exponential smoothing in $L_1$ are generalized using the regression quantiles, including a generalization to more parameters. Then a method based on the classical sign test is introduced that should deal not only with outliers but also with level shifts, including a detection of change points. Properties of various approaches are investigated by means of a simulation study. A real data example is used as an illustration.},
author = {Bejda, Přemysl, Cipra, Tomáš},
journal = {Kybernetika},
keywords = {change point; exponential smoothing; quantiles; robust methods; sign test},
language = {eng},
number = {6},
pages = {973-993},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Exponential smoothing based on L-estimation},
url = {http://eudml.org/doc/276221},
volume = {51},
year = {2015},
}

TY - JOUR
AU - Bejda, Přemysl
AU - Cipra, Tomáš
TI - Exponential smoothing based on L-estimation
JO - Kybernetika
PY - 2015
PB - Institute of Information Theory and Automation AS CR
VL - 51
IS - 6
SP - 973
EP - 993
AB - Robust methods similar to exponential smoothing are suggested in this paper. First previous results for exponential smoothing in $L_1$ are generalized using the regression quantiles, including a generalization to more parameters. Then a method based on the classical sign test is introduced that should deal not only with outliers but also with level shifts, including a detection of change points. Properties of various approaches are investigated by means of a simulation study. A real data example is used as an illustration.
LA - eng
KW - change point; exponential smoothing; quantiles; robust methods; sign test
UR - http://eudml.org/doc/276221
ER -

References

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