Gaussian and Non-Gaussian Linear Time Series and Random Fields

Released on by Murray Rosenblatt
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  • Gaussian and Non-Gaussian Linear Time Series and Random Fields Book Detail

  • Author : Murray Rosenblatt
  • Release Date : 2012-12-06
  • Publisher : Springer Science & Business Media
  • Genre : Mathematics
  • Pages : 252
  • ISBN 13 : 1461212626
  • File Size : 34,34 MB
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Gaussian and Non-Gaussian Linear Time Series and Random Fields by Murray Rosenblatt PDF Summary

Book Description: 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.

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Stationary Sequences and Random Fields

Stationary Sequences and Random Fields

File Size : 59,59 MB
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This book has a dual purpose. One of these is to present material which selec tively will be appropriate for a quarter or semester course in time series analysi