Statistical Analysis of First-Order MARMA Processes
Matematičeskie zametki, Tome 83 (2008) no. 4, pp. 552-558.

Voir la notice de l'article provenant de la source Math-Net.Ru

In this paper, we consider processes of the MARMA type that can be derived from the classical ARMA processes by replacing summation by the maximum operation. It is assumed that the innovations and the values of the process have the standard Fréchet distribution. For simple MARMA processes of first order, certain numerical characteristics are calculated. Sign tests and rank statistical methods for parameter estimation are developed. The characterization relations that can be used for the identification of models are justified.
Keywords: MARMA and ARMA processes, moving maximum, rank test, estimation of parameters, random variable, Pearson correlation coefficient.
Mots-clés : sign test, Fréchet distribution
@article{MZM_2008_83_4_a7,
     author = {A. V. Lebedev},
     title = {Statistical {Analysis} of {First-Order} {MARMA} {Processes}},
     journal = {Matemati\v{c}eskie zametki},
     pages = {552--558},
     publisher = {mathdoc},
     volume = {83},
     number = {4},
     year = {2008},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MZM_2008_83_4_a7/}
}
TY  - JOUR
AU  - A. V. Lebedev
TI  - Statistical Analysis of First-Order MARMA Processes
JO  - Matematičeskie zametki
PY  - 2008
SP  - 552
EP  - 558
VL  - 83
IS  - 4
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/MZM_2008_83_4_a7/
LA  - ru
ID  - MZM_2008_83_4_a7
ER  - 
%0 Journal Article
%A A. V. Lebedev
%T Statistical Analysis of First-Order MARMA Processes
%J Matematičeskie zametki
%D 2008
%P 552-558
%V 83
%N 4
%I mathdoc
%U http://geodesic.mathdoc.fr/item/MZM_2008_83_4_a7/
%G ru
%F MZM_2008_83_4_a7
A. V. Lebedev. Statistical Analysis of First-Order MARMA Processes. Matematičeskie zametki, Tome 83 (2008) no. 4, pp. 552-558. http://geodesic.mathdoc.fr/item/MZM_2008_83_4_a7/

[1] P. Embrechts, C. Klüppelberg, T. Mikosch, Modelling Extremal Events for Insurance and Finance, Appl. Math. (N. Y.), 33, Springer-Verlag, Berlin, 1997 | MR | Zbl

[2] B. Mandelbrot, Fraktalnaya geometriya prirody, In-t kompyuternykh issledovanii, M., 2002 | MR | Zbl

[3] A. J. McNeil, R. Frey, P. Embrechts, Quantitative Risk Management, Concepts, techniques and tools, Princeton Series in Finance, Princeton Univ. Press, Princeton, NJ, 2005 | MR | Zbl

[4] R. A. Davis, S. I. Resnick, “Basic properties and prediction of max-ARMA processes”, Adv. in Appl. Probab., 21:4 (1989), 781–803 | DOI | MR | Zbl

[5] R. A. Davis, S. I. Resnick, “Prediction of stationary max-stable processes”, Ann. Appl. Probab., 3:2 (1993), 497–525 | DOI | MR | Zbl

[6] I. Helland, T. Nilsen, “On a general random exchange model”, J. Appl. Probab., 13:4 (1976), 781–790 | DOI | MR | Zbl

[7] D. Daley, J. Haslet, “A thermal energy storage with controlled input”, Adv. in Appl. Probab., 14:2 (1982), 257–271 | DOI | MR | Zbl

[8] S. G. Coles, “Regional modelling of extreme storms via max-stable processes”, J. Roy. Statist. Soc. Ser. B, 55:4 (1993), 797–816 | MR | Zbl

[9] Z. Zhang, R. L. Smith, Modelling Financial Time Series Data as Moving Maxima Processes, Tech. Rep. Dept. Stat., Univ. North Carolina, Chapel Hill, NC, 2001; http://www.stat.unc.edu/faculty/rs/papers/RLS_Papers.html

[10] M. T. Alpuim, “An extremal Markovian sequence”, J. Appl. Probab., 26:2 (1989), 219–232 | DOI | MR | Zbl

[11] M. T. Alpuim, N. A. Catkan, J. Hüsler, “Extremes and clustering of nonstationary max-AR(1) sequences”, Stochastic Process. Appl., 56:1 (1995), 171–184 | DOI | MR | Zbl

[12] Dzh. Boks, G. Dzhenkins, Analiz vremennykh ryadov, Mir, M., 1974 | MR | MR | Zbl