Asymmetric recursive methods for time series

Tomáš Cipra

Applications of Mathematics (1994)

  • Volume: 39, Issue: 3, page 203-214
  • ISSN: 0862-7940

Abstract

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The problem of asymmetry appears in various aspects of time series modelling. Typical examples are asymmetric time series, asymmetric error distributions and asymmetric loss functions in estimating and predicting. The paper deals with asymmetric modifications of some recursive time series methods including Kalman filtering, exponential smoothing and recursive treatment of Box-Jenkins models.

How to cite

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Cipra, Tomáš. "Asymmetric recursive methods for time series." Applications of Mathematics 39.3 (1994): 203-214. <http://eudml.org/doc/32879>.

@article{Cipra1994,
abstract = {The problem of asymmetry appears in various aspects of time series modelling. Typical examples are asymmetric time series, asymmetric error distributions and asymmetric loss functions in estimating and predicting. The paper deals with asymmetric modifications of some recursive time series methods including Kalman filtering, exponential smoothing and recursive treatment of Box-Jenkins models.},
author = {Cipra, Tomáš},
journal = {Applications of Mathematics},
keywords = {asymmetric recursive methods; time series; Kalman filter; exponential smoothing; asymmetric time series; autoregressive model; split-normal distribution; autoregressive model; split-normal distribution; asymmetric least squares; asymmetric recursive estimation; asymmetric time series; asymmetric error distributions; asymmetric loss functions; recursive time series methods; Kalman filtering; exponential smoothing; recursive treatment of Box-Jenkins models},
language = {eng},
number = {3},
pages = {203-214},
publisher = {Institute of Mathematics, Academy of Sciences of the Czech Republic},
title = {Asymmetric recursive methods for time series},
url = {http://eudml.org/doc/32879},
volume = {39},
year = {1994},
}

TY - JOUR
AU - Cipra, Tomáš
TI - Asymmetric recursive methods for time series
JO - Applications of Mathematics
PY - 1994
PB - Institute of Mathematics, Academy of Sciences of the Czech Republic
VL - 39
IS - 3
SP - 203
EP - 214
AB - The problem of asymmetry appears in various aspects of time series modelling. Typical examples are asymmetric time series, asymmetric error distributions and asymmetric loss functions in estimating and predicting. The paper deals with asymmetric modifications of some recursive time series methods including Kalman filtering, exponential smoothing and recursive treatment of Box-Jenkins models.
LA - eng
KW - asymmetric recursive methods; time series; Kalman filter; exponential smoothing; asymmetric time series; autoregressive model; split-normal distribution; autoregressive model; split-normal distribution; asymmetric least squares; asymmetric recursive estimation; asymmetric time series; asymmetric error distributions; asymmetric loss functions; recursive time series methods; Kalman filtering; exponential smoothing; recursive treatment of Box-Jenkins models
UR - http://eudml.org/doc/32879
ER -

References

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  1. 10.1214/aos/1176345785, Annals of Statistics 10 (1982), 442–453. (1982) Zbl0492.62076MR0653519DOI10.1214/aos/1176345785
  2. Some problems of exponential smoothing, Aplikace matematiky 34 (1989), 161–169. (1989) Zbl0673.62079MR0990303
  3. 10.1002/for.3980110106, Journal of Forecasting 11 (1992), 57–69. (1992) DOI10.1002/for.3980110106
  4. Robust Kalman filter and its application in time series analysis, Kybernetika 27 (1991), 481–494. (1991) MR1150938
  5. Recursive time series methods in L 1 -norm, -Statistical Analysis and Related Methods (Y. Dodge, ed.), North Holland, Amsterdam, 1992, pp. 233–243. (1992) MR1214835
  6. Robustified smoothing and forecasting procedures, Czechoslovak Journal of Operations Research 1 (1992), 41–56. (1992) 
  7. 10.1057/jors.1969.52, Operational Research Quarterly 20 (1969), 199–207. (1969) Zbl0174.21901MR0295497DOI10.1057/jors.1969.52
  8. Multiple Time Series, Wiley, New York, 1970. (1970) Zbl0211.49804MR0279952
  9. 10.1016/0169-2070(89)90067-8, International Journal of Forecasting 5 (1989), 99–110. (1989) DOI10.1016/0169-2070(89)90067-8
  10. 10.2307/1911031, Econometrica 55 (1987), 819–847. (1987) MR0906565DOI10.2307/1911031
  11. A convergence theorem for non negative almost supermartingales and some applications, Optimizing Methods in Statistics (J. S. Rustagi, ed.), Academic Press, New York, 1971, pp. 233–257. (1971) MR0343355
  12. A method for recursive robust estimation of A R -parameters, Preprint, Technical University of Lyngby, Denmark and University of Lund, Sweden, 1990. (1990) 
  13. 10.1016/0378-3758(92)90013-I, Journal of Statistical Planning and Inference 32 (1992), 303–309. (1992) MR1190200DOI10.1016/0378-3758(92)90013-I
  14. 10.1080/01621459.1981.10477595, Journal of the American Statistical Association 76 (1981), 16–21. (1981) DOI10.1080/01621459.1981.10477595

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