|The Physical Object|
|Pagination||xvii, 285 p. :|
|Number of Pages||285|
Long memory time series are characterized by a strong dependence between distant events. Various methods and their theoretical properties are discussed with empirical applications. The methods constitute a very flexible approach to analyzing time series data . I strongly recommend this book to anyone interested in long-memory time series. Both researchers and beginners alike will find this text extremely useful." (Journal of the American Statisticial Association, Dec ) "Very well-organized catalogue of long-memory time series analysis.". Time Series with Long Memory comprises a collection on time series analysis. Long memory time series are characterized by a strong dependence between distant events. Various methods and their theoretical properties are discussed with empirical applications. The methods constitute a very flexible approach to analyzing time series data arising in economics, finance and other fields.4/5(1). This leads quite naturally into a discussion of the autocorrelation function for stationary processes, which is at the core of the investigation. The chapter concludes with a number of real-world examples of long-range dependent time series. Note that the author uses the term "long-memory" to be synonymous with long-range dependence.5/5(4).
This book: Offers beginning-of-chapter examples as well as end-of-chapter technical arguments and proofs; Contains many new results on long memory processes which have not appeared in previous and existing textbooks; Takes a basic mathematics (Calculus) approach to the topic of time series analysis with long memory; Contains 25 illustrative. The authors did an excellent job to reach their goals, and the book would be a must for researchers interested in long-memory processes and practioners on time series and data analysis. the book is an excellent choice for anyone who is working in fields related to long-memory processes with many update information and research topics. Long memory processes have in recent years attracted considerable interest from both theoretical and empirical researchers in time series and econometrics. This book of readings collects articles on a variety of topics in long memory time series including modelling and statistical inference for stationary processes, stochastic volatility models. The Long Memory book. Read reviews from world’s largest community for readers. In it's time a famous novel that was made into a film starring John Mills/5(9).
Long memory time series are characterized by a strong dependence between distant events. This book introduces readers to the theory and foundations of univariate time series analysis with a focus on long memory and fractional integration, which are embedded into the general by: 5. Long memory is a situation that we encounter when we analyze time series data. It is also referred to as Long-range dependence. It basically refers to the level of statistical dependence between two points in the time series. More specifically, it relates to the rate of decay of statistical dependence between the two points as we increase the. A course in Time Series Analysis Suhasini Subba Rao Email: [email protected] November 7, long memory time series, and for further developments, in relation to more general models than () see e.g. Goncalves and Gourieroux (), Lippi and Za⁄aroni (). The rest of the paper deals with various approaches to modelling long memory, for various kinds of data, and with relevant statistical inference. The following section.