Gaussian and Non-Gaussian Linear Time Series and Random Fields /
The book is concerned with linear time series and random fields in both the Gaussian and especially the non-Gaussian context. The principal focus is on autoregressive moving average models and analogous random fields. Probabilistic and statistical questions are both discussed. The Gaussian models ar...
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| Format: | eBook |
| Language: | English |
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New York, NY :
Springer New York,
2000.
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| Series: | Springer series in statistics.
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| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Reversibility and Identifiability
- Minimum Phase Estimation
- Homogeneous Gaussian Random Fields
- Cumulants, Mixing and Estimation for Gaussian Fields
- Prediction for Minimum and Nonminimum Phase Models
- The Fluctuation of the quasi-Gaussian Likelihood
- Random Fields
- Estimation for Possibly Nonminimum Phase Schemes.