Friday 14 February 2014

[P989.Ebook] Get Free Ebook A Practical Guide to Heavy Tails: Statistical Techniques and ApplicationsFrom Brand: Birkh�user

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A Practical Guide to Heavy Tails: Statistical Techniques and ApplicationsFrom Brand: Birkh�user

A Practical Guide to Heavy Tails: Statistical Techniques and ApplicationsFrom Brand: Birkh�user



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A Practical Guide to Heavy Tails: Statistical Techniques and ApplicationsFrom Brand: Birkh�user

Aimed at the general practitioner, A Practical Guide to Heavy Tails is a unique collection of essays that is concerned primarily with a large number of techniques and approaches for data analysis. The expository papers, all by distinguished experts, are intended for a wide audience from different disciplines. Thus, the papers run the gamut of applications of heavy-tailed modeling, e.g., telecommunications, the Web, insurance, finance. Along with specific applications are several papers devoted to time series analysis, regression, classical signal/noise detection problems, and the general structure of stable processes, viewed from a modeling standpoint.

  • Sales Rank: #3731287 in Books
  • Brand: Brand: Birkhäuser
  • Published on: 1998-10-26
  • Original language: English
  • Number of items: 1
  • Dimensions: 10.00" h x 1.19" w x 7.01" l, 2.55 pounds
  • Binding: Hardcover
  • 534 pages
Features
  • Used Book in Good Condition

Review

"The editors and contributors have done a marvelous job… Professional statisticians and applied mathematicians will find it fascinating for its presentation and documentation of versatile methods for handling troublesome data." ―Computing Reviews

Most helpful customer reviews

0 of 0 people found the following review helpful.
opinion about the book
By Igor
There are too many examples and too few theory in the book, but in general it's OK. The book is a kind of block of papers in the field of heavy tails with the emphasis on applications

17 of 23 people found the following review helpful.
Nothing more than a compilation of papers !
By Steve Uhlig
Even if some of the papers whithin the book are certainly important contributions to their field, my impression is that it does not justify paying that price for extended versions of the papers. The book by itself is merely a compilation of the papers but NOTHING MORE ! If you are interested, just get the papers on the web and read them, but don't buy this book !
I hoped i would find some unifying ideas in the book, or even remarks in the extended versions of the papers but nothing... I really wonder how it got published. The only useful information is the extended references for every paper (hence i gave 1 star) ...but it's not worth the price of the book !
I have been extremely disappointed because i'm used to very good work from M. Taqqu, including numerous outstanding papers, but this book is the worst i've ever bought. It does not deserves the name "book".

6 of 9 people found the following review helpful.
AN INTERESTING BOOK ON HEAVY-TAILED DISTRIBUTIONS
By A Customer
In principle, I must confess that I am astonished by the low rating given by the other reviewer! The book is a very good one, emphasizing topics that have not appeared in any other book so far (as, for example, applications of heavy-tailed distributions to financial modeling).
The reason for which I did not give 5 stars is because I am a computer-network specialist, hence I was expecting to see more networking applications than financial ones.
Nevertheless the mathematical content of the book is at a high level; I can assure everyone about it because my first degree is a first-class B.Sc. in Mathematics.
My current job has to do with the design of IP-based multimedia networks and, in fact, I am one of the very few persons (three at most) in the Balkans and probably the only one in Greece who applies the concepts of self-similarity, long-range dependence and heavy-tailed distributions to the design of real communication networks for everyday use. Hence I contend that my opinion matters.
I found particularly helpful the last chapter, which describes numerical techniques. In fact, this is the first book on self-similarity and long-range dependence to address such issues.
I strongly recommend the book for applied mathematicians and financial-modeling experts, while it is quite an interesting reference for network-performance experts. I also recommend it strongly for research students in any of these disciplines.

See all 3 customer reviews...

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