Stationary Sequences and Random Fields:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boston, MA
Birkhäuser Boston
1985
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | This book has a dual purpose. One of these is to present material which selectively will be appropriate for a quarter or semester course in time series analysis and which will cover both the finite parameter and spectral approach. The second object is the presentation of topics of current research interest and some open questions. I mention these now. In particular, there is a discussion in Chapter III of the types of limit theorems that will imply asymptotic normality for covariance estimates and smoothings of the periodogram. This discussion allows one to get results on the asymptotic distribution of finite parameter estimates that are broader than those usually given in the literature in Chapter IV. A derivation of the asymptotic distribution for spectral (second order) estimates is given under an assumption of strong mixing in Chapter V. A discussion of higher order cumulant spectra and their large sample properties under appropriate moment conditions follows in Chapter VI. Probability density, conditional probability density and regression estimates are considered in Chapter VII under conditions of short range dependence. Chapter VIII deals with a number of topics. At first estimates for the structure function of a large class of non-Gaussian linear processes are constructed. One can determine much more about this structure or transfer function in the non-Gaussian case than one can for Gaussian processes. In particular, one can determine almost all the phase information |
| Beschreibung: | 1 Online-Ressource (264p) |
| ISBN: | 9781461251569 9780817632649 |
| DOI: | 10.1007/978-1-4612-5156-9 |
Internformat
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Datensatz im Suchindex
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| author | Rosenblatt, Murray |
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| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4612-5156-9 |
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| id | DE-604.BV042420367 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:21:06Z |
| institution | BVB |
| isbn | 9781461251569 9780817632649 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027855784 |
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| publishDate | 1985 |
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| spelling | Rosenblatt, Murray Verfasser aut Stationary Sequences and Random Fields by Murray Rosenblatt Boston, MA Birkhäuser Boston 1985 1 Online-Ressource (264p) txt rdacontent c rdamedia cr rdacarrier This book has a dual purpose. One of these is to present material which selectively will be appropriate for a quarter or semester course in time series analysis and which will cover both the finite parameter and spectral approach. The second object is the presentation of topics of current research interest and some open questions. I mention these now. In particular, there is a discussion in Chapter III of the types of limit theorems that will imply asymptotic normality for covariance estimates and smoothings of the periodogram. This discussion allows one to get results on the asymptotic distribution of finite parameter estimates that are broader than those usually given in the literature in Chapter IV. A derivation of the asymptotic distribution for spectral (second order) estimates is given under an assumption of strong mixing in Chapter V. A discussion of higher order cumulant spectra and their large sample properties under appropriate moment conditions follows in Chapter VI. Probability density, conditional probability density and regression estimates are considered in Chapter VII under conditions of short range dependence. Chapter VIII deals with a number of topics. At first estimates for the structure function of a large class of non-Gaussian linear processes are constructed. One can determine much more about this structure or transfer function in the non-Gaussian case than one can for Gaussian processes. In particular, one can determine almost all the phase information Mathematics Field theory (Physics) Sequences (Mathematics) Sequences, Series, Summability Field Theory and Polynomials Mathematik Stationärer Prozess (DE-588)4056989-5 gnd rswk-swf Zufälliges Feld (DE-588)4191094-1 gnd rswk-swf Zeitreihenanalyse (DE-588)4067486-1 gnd rswk-swf Zeitreihenanalyse (DE-588)4067486-1 s Zufälliges Feld (DE-588)4191094-1 s Stationärer Prozess (DE-588)4056989-5 s 1\p DE-604 https://doi.org/10.1007/978-1-4612-5156-9 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Rosenblatt, Murray Stationary Sequences and Random Fields Mathematics Field theory (Physics) Sequences (Mathematics) Sequences, Series, Summability Field Theory and Polynomials Mathematik Stationärer Prozess (DE-588)4056989-5 gnd Zufälliges Feld (DE-588)4191094-1 gnd Zeitreihenanalyse (DE-588)4067486-1 gnd |
| subject_GND | (DE-588)4056989-5 (DE-588)4191094-1 (DE-588)4067486-1 |
| title | Stationary Sequences and Random Fields |
| title_auth | Stationary Sequences and Random Fields |
| title_exact_search | Stationary Sequences and Random Fields |
| title_full | Stationary Sequences and Random Fields by Murray Rosenblatt |
| title_fullStr | Stationary Sequences and Random Fields by Murray Rosenblatt |
| title_full_unstemmed | Stationary Sequences and Random Fields by Murray Rosenblatt |
| title_short | Stationary Sequences and Random Fields |
| title_sort | stationary sequences and random fields |
| topic | Mathematics Field theory (Physics) Sequences (Mathematics) Sequences, Series, Summability Field Theory and Polynomials Mathematik Stationärer Prozess (DE-588)4056989-5 gnd Zufälliges Feld (DE-588)4191094-1 gnd Zeitreihenanalyse (DE-588)4067486-1 gnd |
| topic_facet | Mathematics Field theory (Physics) Sequences (Mathematics) Sequences, Series, Summability Field Theory and Polynomials Mathematik Stationärer Prozess Zufälliges Feld Zeitreihenanalyse |
| url | https://doi.org/10.1007/978-1-4612-5156-9 |
| work_keys_str_mv | AT rosenblattmurray stationarysequencesandrandomfields |