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Taniguchi, Masanobu; Kakizawa, Yoshihide - Asymptotic Theory of Statistical Inference for Time Series - 9781461270287 - V9781461270287
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Asymptotic Theory of Statistical Inference for Time Series

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Description for Asymptotic Theory of Statistical Inference for Time Series Paperback. Series: Springer Series in Statistics. Num Pages: 679 pages, biography. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 34. Weight in Grams: 1032.
There has been much demand for the statistical analysis of dependent ob­ servations in many fields, for example, economics, engineering and the nat­ ural sciences. A model that describes the probability structure of a se­ ries of dependent observations is called a stochastic process. The primary aim of this book is to provide modern statistical techniques and theory for stochastic processes. The stochastic processes mentioned here are not restricted to the usual autoregressive (AR), moving average (MA), and autoregressive moving average (ARMA) processes. We deal with a wide variety of stochastic processes, for example, non-Gaussian linear processes, long-memory processes, nonlinear ... Read more

Product Details

Format
Paperback
Publication date
2012
Publisher
Springer-Verlag New York Inc. United States
Number of pages
679
Condition
New
Series
Springer Series in Statistics
Number of Pages
662
Place of Publication
New York, NY, United States
ISBN
9781461270287
SKU
V9781461270287
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

Reviews for Asymptotic Theory of Statistical Inference for Time Series
From the reviews: MATHEMATICAL REVIEWS "It is valuable both as an advanced graduate level text and as a reference for researchers?he book can be most strongly recommended."

Goodreads reviews for Asymptotic Theory of Statistical Inference for Time Series


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