Title:
|
Robust Kalman filter and its application in time series analysis (English) |
Author:
|
Cipra, Tomáš |
Author:
|
Romera, Rosario |
Language:
|
English |
Journal:
|
Kybernetika |
ISSN:
|
0023-5954 |
Volume:
|
27 |
Issue:
|
6 |
Year:
|
1991 |
Pages:
|
481-494 |
. |
Category:
|
math |
. |
MSC:
|
62F35 |
MSC:
|
62M20 |
MSC:
|
93E11 |
idZBL:
|
Zbl 0745.62090 |
idMR:
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MR1150938 |
. |
Date available:
|
2009-09-24T18:28:22Z |
Last updated:
|
2012-06-05 |
Stable URL:
|
http://hdl.handle.net/10338.dmlcz/124292 |
. |
Reference:
|
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Reference:
|
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Reference:
|
[3] A. E. Bryson, J. C. Ho: Applied Optimal Control.J. Wiley, New York 1975. MR 0446628 |
Reference:
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[4] K. Campbell: Recursive computation of M-estimates for the parameters of a finite autoregressive process.Ann. Statist. 10 (1982), 442-453. Zbl 0492.62076, MR 0653519 |
Reference:
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[5] J. E. Englund: Multivariate Recursive M-estimators of Location and Scatter for Dependent Sequences.Research Report, University of Lund and Lund Institute of Technology 1988. |
Reference:
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[6] A. A. Ershov, R. S. Liptser: Robust Kalman filter in discrete time.Automat. Remote Control 39 (1978), 359-367. Zbl 0417.93070 |
Reference:
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[7] E. J. Hannan: Multiple Time Series.J. Wiley, New York 1970. Zbl 0211.49804, MR 0279952 |
Reference:
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[8] P. J. Harrison, C. F. Stevens: Bayesian forecasting.J. Roy. Statist. Soc. Ser. B 38 (1976), 205-247. Zbl 0349.62062, MR 0655429 |
Reference:
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[9] U. Holst: Convergence of a recursive stochastic algorithm with m-dependent observations.Scand. J. Statist. 7 (1980), 207-215. Zbl 0455.62065, MR 0605992 |
Reference:
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[10] U. Hoist: Convergence of a recursive robust algorithm with strongly regular observations.Stochastic Process. Appl. 16 (1984), 305-320. MR 0723851 |
Reference:
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[11] P. J. Huber: Robust Statistics.J. Wiley, New York 1981. Zbl 0536.62025, MR 0606374 |
Reference:
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[12] R. D. Martin: Robust estimation for time series autoregressions.In: Robustness in Statistics (R. L. Launer and G. N. Wilkinson, eds.), Academic Press, New York 1979, pp. 147-176. |
Reference:
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[13] C. J. Masreliez: Approximate non-Gaussian filtering with linear state and observation relations.IEEE Trans. Automat. Control AC-20 (1975), 107-110. Zbl 0298.93018 |
Reference:
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[14] C. J. Masreliez, R. D. Martin: Robust Bayesian estimation for the linear model and robustifying the Kalman filter.IEEE Trans. Automat. Control AC-22 (1977), 361 - 371. Zbl 0354.93054, MR 0453124 |
Reference:
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[15] R. J. Meinhold, N. D. Singpurwalla: Robustification of Kalman filter models.J. Amer. Statist. Assoc. 84 (1989), 479-486. MR 1010336 |
Reference:
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[16] M. Pantel: Adaptive Verfahren der stochastischen Approximation.Dissertation, Universitiit Essen 1979. |
Reference:
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[17] D. Peňa, J. Guttman: Optimal collapsing of mixture distributions in robust recursive estimation.Comm. Statist. Theory Methods 18 (1989), 817-833. MR 1001623 |
Reference:
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[18] B. T. Polyak, Ya. Z. Tsypkin: Adaptive estimation algorithms: convergence, optimality, stability (in Russian).Avtomat. Telemekh. (1979), 3, 71-84. MR 0544876 |
Reference:
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[19] B. T. Polyak, Ya. Z. Tsypkin: Optimal methods of estimation of autoregressive parameters under incomplete information (in Russian).Tekh. kibernet. (1983), 1, 118-126. MR 0736269 |
Reference:
|
[20] H. Robbins, D. Siegmund: A convergence theorem for non negative almost supermartingales and some applications.In: Optimizing Methods in Statistics (J. S. Rustagi, ed.), Academic Press, New York 1971, pp. 233 - 257. Zbl 0286.60025, MR 0343355 |
Reference:
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[21] L. D. Servi, Y. C. Ho: Recursive estimation in the presence of uniformly distributed measurement noise.IEEE Trans. Automat. Control AC-26 (1981), 563-565. Zbl 0475.93065, MR 0613583 |
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