Statistics For Long Memory Processes

Statistics For Long Memory Processes by Jan Beran. Download in PDF, EPUB, and Mobi Format for read it on your Kindle device, PC, phones or tablets. Statistics For Long Memory Processes books. Click Download for free ebooks.

Statistics For Long Memory Processes

Statistics For Long Memory Processes
Author: Jan Beran
Publisher: CRC Press
ISBN: 9780412049019
Size: 34.21 MB
Format: PDF, ePub
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Statistical Methods for Long Term Memory Processes covers the diverse statistical methods and applications for data with long-range dependence. Presenting material that previously appeared only in journals, the author provides a concise and effective overview of probabilistic foundations, statistical methods, and applications. The material emphasizes basic principles and practical applications and provides an integrated perspective of both theory and practice. This book explores data sets from a wide range of disciplines, such as hydrology, climatology, telecommunications engineering, and high-precision physical measurement. The data sets are conveniently compiled in the index, and this allows readers to view statistical approaches in a practical context. Statistical Methods for Long Term Memory Processes also supplies S-PLUS programs for the major methods discussed. This feature allows the practitioner to apply long memory processes in daily data analysis. For newcomers to the area, the first three chapters provide the basic knowledge necessary for understanding the remainder of the material. To promote selective reading, the author presents the chapters independently. Combining essential methodologies with real-life applications, this outstanding volume is and indispensable reference for statisticians and scientists who analyze data with long-range dependence.
Statistics for Long-Memory Processes
Language: en
Pages: 315
Authors: Jan Beran
Categories: Mathematics
Type: BOOK - Published: 1994-10-01 - Publisher: CRC Press
Statistical Methods for Long Term Memory Processes covers the diverse statistical methods and applications for data with long-range dependence. Presenting material that previously appeared only in journals, the author provides a concise and effective overview of probabilistic foundations, statistical methods, and applications. The material emphasizes basic principles and practical applications
Large Sample Inference For Long Memory Processes
Language: en
Pages: 596
Authors: Donatas Surgailis, Hira L Koul, Liudas Giraitis
Categories: Mathematics
Type: BOOK - Published: 2012-04-27 - Publisher: World Scientific Publishing Company
Box and Jenkins (1970) made the idea of obtaining a stationary time series by differencing the given, possibly nonstationary, time series popular. Numerous time series in economics are found to have this property. Subsequently, Granger and Joyeux (1980) and Hosking (1981) found examples of time series whose fractional difference becomes
Long-Memory Processes
Language: en
Pages: 884
Authors: Jan Beran, Yuanhua Feng, Sucharita Ghosh, Rafal Kulik
Categories: Mathematics
Type: BOOK - Published: 2013-05-14 - Publisher: Springer Science & Business Media
Long-memory processes are known to play an important part in many areas of science and technology, including physics, geophysics, hydrology, telecommunications, economics, finance, climatology, and network engineering. In the last 20 years enormous progress has been made in understanding the probabilistic foundations and statistical principles of such processes. This book
Inference on Long Memory Processes
Language: en
Pages: 226
Authors: Hongwen Guo
Categories: Electronic dissertations
Type: BOOK - Published: 2006 - Publisher:
Books about Inference on Long Memory Processes
Dependence in Probability and Statistics
Language: en
Pages: 205
Authors: Paul Doukhan, Gabriel Lang, Donatas Surgailis, Gilles Teyssière
Categories: Mathematics
Type: BOOK - Published: 2010-07-23 - Publisher: Springer Science & Business Media
This account of recent works on weakly dependent, long memory and multifractal processes introduces new dependence measures for studying complex stochastic systems and includes other topics such as the dependence structure of max-stable processes.
Extreme Value Methods with Applications to Finance
Language: en
Pages: 399
Authors: Serguei Y. Novak
Categories: Mathematics
Type: BOOK - Published: 2011-12-20 - Publisher: CRC Press
Extreme value theory (EVT) deals with extreme (rare) events, which are sometimes reported as outliers. Certain textbooks encourage readers to remove outliers—in other words, to correct reality if it does not fit the model. Recognizing that any model is only an approximation of reality, statisticians are eager to extract information
Environmental Modelling
Language: en
Pages: 496
Authors: John Wainwright, Mark Mulligan
Categories: Technology & Engineering
Type: BOOK - Published: 2013-01-22 - Publisher: John Wiley & Sons
Simulation models are an established method used to investigate processes and solve practical problems in a wide variety of disciplines. Central to the concept of this second edition is the idea that environmental systems are complex, open systems. The authors present the diversity of approaches to dealing with environmental complexity
Semimartingales and their Statistical Inference
Language: en
Pages: 450
Authors: B.L.S. Prakasa Rao
Categories: Mathematics
Type: BOOK - Published: 1999-05-11 - Publisher: CRC Press
Statistical inference carries great significance in model building from both the theoretical and the applications points of view. Its applications to engineering and economic systems, financial economics, and the biological and medical sciences have made statistical inference for stochastic processes a well-recognized and important branch of statistics and probability. The
Wavelet Methods for Time Series Analysis
Language: en
Pages: 620
Authors: Donald B. Percival, Andrew T. Walden
Categories: Mathematics
Type: BOOK - Published: 2006-02-27 - Publisher: Cambridge University Press
This introduction to wavelet analysis 'from the ground level and up', and to wavelet-based statistical analysis of time series focuses on practical discrete time techniques, with detailed descriptions of the theory and algorithms needed to understand and implement the discrete wavelet transforms. Numerous examples illustrate the techniques on actual time
Introductory Time Series with R
Language: en
Pages: 256
Authors: Paul S.P. Cowpertwait, Andrew V. Metcalfe
Categories: Mathematics
Type: BOOK - Published: 2009-05-28 - Publisher: Springer Science & Business Media
This book gives you a step-by-step introduction to analysing time series using the open source software R. Each time series model is motivated with practical applications, and is defined in mathematical notation. Once the model has been introduced it is used to generate synthetic data, using R code, and these