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Luz / Moklyachuk

Non-Stationary Stochastic Processes Estimation

Vector Stationary Increments, Periodically Stationary Multi-Seasonal Increments

Medium: Buch
ISBN: 978-3-11-132533-0
Verlag: De Gruyter
Erscheinungstermin: 20.05.2024
Lieferfrist: bis zu 10 Tage
The problem of forecasting future values of economic and physical processes, the problem of restoring lost information, cleaning signals or other data observations from noise, is magnified in an information-laden word. Methods of stochastic processes estimation depend on two main factors. The first factor is construction of a model of the process being investigated. The second factor is the available information about the structure of the process under consideration. In this book, we propose results of the investigation of the problem of mean square optimal estimation (extrapolation, interpolation, and filtering) of linear functionals depending on unobserved values of stochastic sequences and processes with periodically stationary and long memory multiplicative seasonal increments. Formulas for calculating the mean square errors and the spectral characteristics of the optimal estimates of the functionals are derived in the case of spectral certainty, where spectral structure of the considered sequences and processes are exactly known. In the case where spectral densities of the sequences and processes are not known exactly while some sets of admissible spectral densities are given, we apply the minimax-robust method of estimation.


  • Artikelnummer: 9783111325330
  • Medium: Buch
  • ISBN: 978-3-11-132533-0
  • Verlag: De Gruyter
  • Erscheinungstermin: 20.05.2024
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2024
  • Serie: De Gruyter Textbook
  • Produktform: Kartoniert
  • Gewicht: 514 g
  • Seiten: 292
  • Format (B x H): 170 x 240 mm
  • Ausgabetyp: Kein, Unbekannt



Luz, Maksym

Moklyachuk, Mikhail