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190928s2019 nju o 000 0 eng d |
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|a 9781119663522
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|a 1119663520
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|a (OCoLC)1121130306
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|a 519.2
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|a UAMI
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|a Luz, Maksym.
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|a Estimates of Stochastic Processes with Stationary Increments and Cointegrated Sequences
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|a Newark :
|b John Wiley & Sons, Incorporated,
|c 2019.
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|a 1 online resource (313 pages)
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|a text
|b txt
|2 rdacontent
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|a computer
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|a Print version record.
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|6 880-01
|a Cover; Half-Title Page; Title Page; Copyright Page; Contents; Notations; Introduction; 1. Stationary Increments of Discrete Time Stochastic Processes: Spectral Representation; 2. Extrapolation Problem for Stochastic Sequences with Stationary nth Increments; 2.1. The classical method of extrapolation; 2.2. Minimax (robust) method of extrapolation; 2.3. Least favorable spectral density in the class D0ƒ; 2.4. Least favorable spectral densities which admit factorization in the class D0ƒ; 2.5. Least favorable spectral density in the class Duv
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|a 2.6. Least favorable spectral density which admits factorization in the class Duv3. Interpolation Problem for Stochastic Sequences with Stationary nth Increments; 3.1. The classical method of interpolation; 3.2. Minimax method of interpolation; 3.3. Least favorable spectral densities in the class D-0,n; 3.4. Least favorable spectral densities in the class D-M, n; 4. Extrapolation Problem for Stochastic Sequences with Stationary nth Increments Based on Observations with Stationary Noise; 4.1. The classical method of extrapolation with noise
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590 |
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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650 |
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|a Stochastic processes.
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650 |
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|a Processus stochastiques.
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650 |
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|a Stochastic processes
|2 fast
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700 |
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|a Moklyachuk, Mikhail.
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758 |
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|i has work:
|a Estimation of stochastic processes with stationary increments and cointegrated sequences (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCFyyR8RxWkGdvRtyhf8CFC
|4 https://id.oclc.org/worldcat/ontology/hasWork
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776 |
0 |
8 |
|i Print version:
|a Luz, Maksym.
|t Estimates of Stochastic Processes with Stationary Increments and Cointegrated Sequences.
|d Newark : John Wiley & Sons, Incorporated, ©2019
|z 9781786305039
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856 |
4 |
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|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=5904681
|z Texto completo
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880 |
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|6 505-00/Grek
|a 4.2. Extrapolation of cointegrated stochastic sequences4.3. Minimax (robust) method of extrapolation; 4.4. Least favorable spectral densities in the class D0ƒ × D0g; 4.5. Least favorable spectral densities which admit factorization in the class D0ƒ × D0g; 4.6. Least favorable spectral densities in the class Duv × Dϵ; 4.7. Least favorable spectral densities which admit factorization in the class Duv × Dϵ; 5. Interpolation Problem for Stochastic Sequences with Stationary nth Increments Based on Observations with Stationary Noise; 5.1. The classical method of interpolation with noise
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|6 505-00/Grek
|a 5.2. Interpolation of cointegrated stochastic sequences5.3. Minimax (robust) method of interpolation; 5.4. Least favorable spectral densities in the class D-0,ƒ × D-0,g; 5.5. Least favorable spectral densities in the class D2ϵ1 × D1ϵ2; 6. Filtering Problem of Stochastic Sequences with Stationary nth Increments Based on Observations with Stationary Noise; 6.1. The classical method of filtering; 6.2. Filtering problem for cointegrated stochastic sequences; 6.3. Minimax (robust) method of filtering; 6.4. Least favorable spectral densities in the class D0ƒ × D0g
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|6 505-00/Grek
|a 6.5. Least favorable spectral densities which admit factorization in the class D0ƒ × D0g6.6. Least favorable spectral densities in the class Duv × Dϵ; 6.7. Least favorable spectral densities which admit factorization in the class Duv × Dϵ; 7. Interpolation Problem for Stochastic Sequences with Stationary nth Increments Observed with Non-stationary Noise; 7.1. The classical interpolation problem in the case of non-stationary noise; 7.2. Minimax (robust) method of interpolation; 7.3. Least favorable spectral densities in the class D-0,μ × D-0,μ
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|6 505-01/(S
|a 7.4. Least favorable spectral densities in the class D-M, μ × D- M, μ
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938 |
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|a ProQuest Ebook Central
|b EBLB
|n EBL5904681
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994 |
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|a 92
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