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Asymptotic Theory of Statistical Inference for Time Series
Taniguchi, Masanobu; Kakizawa, Yoshihide
€ 198.12
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Description for Asymptotic Theory of Statistical Inference for Time Series
Hardback. This title is a research-level monograph suitable as a reference on time- series analysis and the statistical analysis of stochastic processes. It should be useful to Masters and PhD statistics students, as well as researchers in areas such as financial engineering and seismology. Series: Springer Series in Statistics. Num Pages: 679 pages, biography. BIC Classification: PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 238 x 169 x 42. Weight in Grams: 1106.
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
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
Hardback
Publication date
2000
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
9780387950396
SKU
V9780387950396
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."