Gaussian and Non-Gaussian Linear Time Series and Random Fields (2000) (Springer Series in Statistics)
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- Synopsis
- The principal focus here is on autoregressive moving average models and analogous random fields, with probabilistic and statistical questions also being discussed. The book contrasts Gaussian models with noncausal or noninvertible (nonminimum phase) non-Gaussian models and deals with problems of prediction and estimation. New results for nonminimum phase non-Gaussian processes are exposited and open questions are noted. Intended as a text for gradutes in statistics, mathematics, engineering, the natural sciences and economics, the only recommendation is an initial background in probability theory and statistics. Notes on background, history and open problems are given at the end of the book.
- Copyright:
- 2000
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9781461212621
- Related ISBNs:
- 9780387989174
- Publisher:
- Springer New York
- Date of Addition:
- 12/21/20
- Copyrighted By:
- N/A
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Mathematics and Statistics
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.