Sequential monitoring for change in scale

Ondřej Chochola

Kybernetika (2008)

  • Volume: 44, Issue: 5, page 715-730
  • ISSN: 0023-5954

Abstract

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We propose a sequential monitoring scheme for detecting a change in scale. We consider a stable historical period of length m . The goal is to propose a test with asymptotically small probability of false alarm and power 1 as the length of the historical period tends to infinity. The asymptotic distribution under the null hypothesis and consistency under the alternative hypothesis is derived. A small simulation study illustrates the finite sample performance of the monitoring scheme.

How to cite

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Chochola, Ondřej. "Sequential monitoring for change in scale." Kybernetika 44.5 (2008): 715-730. <http://eudml.org/doc/33959>.

@article{Chochola2008,
abstract = {We propose a sequential monitoring scheme for detecting a change in scale. We consider a stable historical period of length $m$. The goal is to propose a test with asymptotically small probability of false alarm and power 1 as the length of the historical period tends to infinity. The asymptotic distribution under the null hypothesis and consistency under the alternative hypothesis is derived. A small simulation study illustrates the finite sample performance of the monitoring scheme.},
author = {Chochola, Ondřej},
journal = {Kybernetika},
keywords = {sequential test for change in scale},
language = {eng},
number = {5},
pages = {715-730},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Sequential monitoring for change in scale},
url = {http://eudml.org/doc/33959},
volume = {44},
year = {2008},
}

TY - JOUR
AU - Chochola, Ondřej
TI - Sequential monitoring for change in scale
JO - Kybernetika
PY - 2008
PB - Institute of Information Theory and Automation AS CR
VL - 44
IS - 5
SP - 715
EP - 730
AB - We propose a sequential monitoring scheme for detecting a change in scale. We consider a stable historical period of length $m$. The goal is to propose a test with asymptotically small probability of false alarm and power 1 as the length of the historical period tends to infinity. The asymptotic distribution under the null hypothesis and consistency under the alternative hypothesis is derived. A small simulation study illustrates the finite sample performance of the monitoring scheme.
LA - eng
KW - sequential test for change in scale
UR - http://eudml.org/doc/33959
ER -

References

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  1. Chochola O., Rekurzivní postupy pro detekci změny rozdělení (Recursive Procedures for Detection of Changes), Master’s Thesis. Faculty of Mathematics and Physics, Charles University, Prague 2007 
  2. Chow Y. S., Teicher H., Probability Theory: Independence, Interchangeability, Martingales, Third edition. Springer, New York 2003 Zbl1049.60001
  3. Chu C.-S. J., Stinchcombe, M., White H., Monitoring structural change, Econometrica 64 (1996), 1045–1065 (1996) Zbl0856.90027
  4. Horváth L., Hušková M., Kokoszka, M., Steinebach J., Monitoring changes in linear models, J. Stat. Plann. Inference 126 (2004), 225–251 Zbl1075.62054MR2090695
  5. Horváth L., Kokoszka, P., Steinebach J., On sequential detection of parameter changes in linear regression, Statist. Probab. Lett. 77 (2007), 885–895 Zbl1117.62079MR2363438
  6. Koubková A., Sequential Change-Point Analysis, Ph.D. Thesis. Faculty of Mathematics and Physics, Charles University, Prague 2006 
  7. Leisch F., Hornik, K., Kuan E. M., Monitoring structural changes with the generalized fluctuation test, Econometric Theory 16 (2000), 835–854 Zbl0967.62067MR1803712
  8. Zeileis A., Kleiber C., Krämer, W., Hornik K., Testing and dating of structural changes in practice, Comput. Statist. Data Anal. 44 (2003), 1–2, 109–123 MR2019790
  9. Zeileis A., Leisch F., Hornik, K., Kleiber C., Strucchange: An r package for testing for structural change in linear regression models, J. Statist. Software 7 (2002), 2 
  10. Zeileis A., Leisch F., Kleiber, C., Hornik K., Monitoring structural change in dynamic econometric models, J. Appl. Econometrics 20 (1005), 99–121 MR2138205

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