Non-stationary stochastic processes estimation vector stationary increments, periodically stationary multi-seasonal increments
Non-stationary stochastic processes estimation: vector stationary increments, periodically stationary multi-seasonal increments

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...

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Bibliographische Detailangaben
Hauptverfasser: Luz, Maksym (VerfasserIn), Moklyachuk, Mikhail (VerfasserIn)
Format: Elektronisch E-Book
Sprache:English
Veröffentlicht: Berlin ; Boston De Gruyter [2024]
© 2024
Schriftenreihe:De Gruyter Textbook
Schlagworte:
Minimax Spektrale Eigenschaften
Prognose
Ungünstigste spektrale Dichte
minimax-robuste Schätzung
periodisch stationäre Inkremente
BUSINESS & ECONOMICS / Statistics
Online-Zugang:DE-1043
DE-1046
DE-858
DE-Aug4
DE-898
DE-859
DE-860
DE-91
DE-473
DE-703
DE-20
DE-739
Volltext
Zusammenfassung: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
Beschreibung:1 Online-Ressource (XVIII, 292 Seiten)
ISBN:9783111325620
9783111326252
DOI:10.1515/9783111325620

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