Last edited by Nacage
Tuesday, May 12, 2020 | History

5 edition of High performance discovery in time series found in the catalog.

High performance discovery in time series

techniques and case studies

by Dennis Elliott Shasha

  • 399 Want to read
  • 0 Currently reading

Published by Springer in New York .
Written in English

    Subjects:
  • Time series analysis

  • Edition Notes

    Includes bibliographical references (p. [181]-187) and index.

    StatementDennis Shasha, Yunyue Zhu.
    SeriesMonographs in computer science
    ContributionsZhu, Yunyue.
    Classifications
    LC ClassificationsQA280 .S53 2004
    The Physical Object
    Paginationix, 190 p. :
    Number of Pages190
    ID Numbers
    Open LibraryOL3382583M
    ISBN 100387008578
    LC Control Number2004556616
    OCLC/WorldCa56035818

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High performance discovery in time series by Dennis Elliott Shasha Download PDF EPUB FB2

High Performance Discovery in Time Series presents rapid-discovery techniques for finding portions of time series with many events (i.e., gamma-ray scatterings) and finding closely related time series (i.e., highly correlated price and return histories, or musical melodies).

A typical time-series technique may compute a "consensus" time series 5/5(2). A typical time-series technique may compute a "consensus" time series—from a collection of time series—to use regression analysis for predicting future time points.

By contrast, this book aims at efficient discovery in time series, rather than prediction, and its novelty lies in its algorithmic contributions and its simple, practical.

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Free shipping for many products. Get this from a library. High performance discovery in time series: techniques and case studies. [Dennis Elliott Shasha; Yunyue Zhu] -- "This new monograph provides a technical survey of concepts and techniques for describing and analyzing large scale time-series data streams.

It offers essential coverage of the topic for computer. This monograph is a technical survey of concepts and techniques for describing and analyzing large-scale time-series data streams.

Some topics covered are algorithms for query by humming, gamma-ray burst detection, pairs trading, and density detection. Included are self-contained descriptions Price: $   Read High Performance Discovery In Time Series Techniques and Case Studies Monographs in Ebook Online.

High Performance Discovery In Time Series 作者: New York University 出版社: Springer 副标题: Techniques and Case Studies 出版年: 页数: 定价: GBP 装帧:.

High Performance Data Mining in Time Series: Techniques and Case Studies by Yunyue Zhu A dissertation submitted in partial fulflllment of the requirements for the degree of Doctor of Philosophy Department of Computer Science New York University January Dennis Shasha °File Size: 1MB.

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There are some good, free, online resources: The Little Book of R for Time Series, by Avril Coghlan (also available in print, reasonably cheap) - I haven't read through this all, but it looks like it's well written, has some good examples, and starts basically from scratch (ie.

easy to get into).; Chap Statistics with R, by Vincent Zoonekynd - Decent intro, but probably slightly more. All the parts within any engine are designed and engineered using the appropriate mathematics to function efficiently and be durable. When discussing high-performance automotive engines, a specific set of math formulas are used to develop and design power plants to make more power at higher rpm levels and still survive.

The various forms of motorsport and street use all have different.Land Rover Discovery, in slang or popular language also frequently just called "Disco", is a series of mid-size luxury SUVs, produced under the Land Rover marque, from the British manufacturer Land Rover (becoming Jaguar Land Rover in ).

The vehicle series has seen five iterations (or generations, according to the manufacturer), the first of which was introduced inheavily based on Class: Mid-size luxury SUV.I think the mainstay textbook on this (for economists anyway) is James Hamilton's Time Series Analysis [1].

If this is your passion, do get it. However, it's long and very dry and for a first-timer, not great to read at all.

If you're just inter.