Gaussian and Non-Gaussian Linear Time Series and Random Fields (Springer Series in Statistics)

by Murray Rosenblatt

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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.
  • ISBN10 1461212634
  • ISBN13 9781461212638
  • Publish Date 21 December 1999
  • Publish Status Withdrawn
  • Out of Print 18 October 2014
  • Publish Country US
  • Imprint Springer My Copy UK
  • Format Paperback (US Trade)
  • Pages 264
  • Language English