Long-Range Dependence and Self-Similarity
Long-Range Dependence and Self-Similarity is a Cambridge University Press book for graduate students and researchers studying probability and stochastic processes. It progresses from foundational material to research-focused topics, with exercises in each chapter.
At a glance
- Covers foundational concepts and more specialized, current research topics in long-range dependence and self-similarity.
- Topics include limit theorems for long-range dependent series, Hermite processes, fractional Brownian motion and its stochastic calculus.
- Also addresses multidimensional models, decompositions of fractional Brownian motion and maximum likelihood estimation for long-range dependent time series.
- Each chapter includes exercises, including some that invite consideration of open research problems.
Pros and cons
Pros
- Broad scope links core concepts with specialized topics relevant to research.
- Chapter exercises provide opportunities to check understanding and engage with open problems.
Technical specifications
9 specifications| Publisher | Cambridge University Press |
|---|---|
| Publication date | April 18, 2017 |
| Edition | 1st |
| Language | English |
| Print length | 688 pages |
| ISBN-10 | 1107039460 |
| ISBN-13 | 978-1107039469 |
| Weight listed | 3.13 pounds |
|---|---|
| Dimensions | 7.25 x 1.75 x 10 inches |
What to know before buying
- The description positions this as a graduate-level and research-oriented text. Readers seeking an introductory, nontechnical treatment may find its intended scope a poor fit. The listing provides no prerequisite details.
Who is it for?
A good fit for
- Graduate students in probability, statistics or related mathematical fields.
- Researchers working with long-range dependent time series, self-similarity or fractional Brownian motion.
Less suited to
- Readers looking for a general-audience introduction or a clearly specified prerequisite-free textbook.
Customer reviews on Amazon
- 5 stars
66% 66% - 4 stars
0% 0% - 3 stars
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34% 34%
Aggregate customer ratings are sharply divided, with both five-star and one-star ratings represented and no middle-star ratings in the supplied distribution. The small rating sample does not explain the reasons behind those opinions, so it offers limited guidance on the book's suitability. Its described graduate and research focus is the clearest buying consideration.
Frequently asked questions
What topics does the book cover?
The listing describes long-range dependence and self-similarity, limit theorems, Hermite processes, fractional Brownian motion and stochastic calculus, multidimensional models, and estimation methods for long-range dependent time series.
Who is this book intended for?
It is described as designed for graduate students and researchers. The listing does not specify prerequisites.
Are exercises included?
Yes. The description says each chapter has numerous exercises, including exercises for checking understanding and considering open research problems.
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