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Basic data analysis for time series ...
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Derryberry, DeWayne R.,
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Basic data analysis for time series with R
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Basic data analysis for time series with R/ DeWayne R. Derryberry.
作者:
Derryberry, DeWayne R.,
出版者:
Hoboken, New Jersey :John Wiley & Sons, Inc., : 2014.,
面頁冊數:
1 online resource.
標題:
Time-series analysis - Data processing. -
電子資源:
http://onlinelibrary.wiley.com/book/10.1002/9781118593233
ISBN:
9781118593370 (pdf)
Basic data analysis for time series with R
Derryberry, DeWayne R.,
Basic data analysis for time series with R
[electronic resource] /DeWayne R. Derryberry. - Hoboken, New Jersey :John Wiley & Sons, Inc.,2014. - 1 online resource.
Includes bibliographical references and index.
"This book emphasizes the collaborative analysis of data that is used to collect increments of time or space. Written at a readily accessible level, but with the necessary theory in mind, the author uses frequency- and time-domain and trigonometric regression as themes throughout the book. The content includes modern topics such as wavelets, Fourier series, and Akaike's Information Criterion (AIC), which is not typical of current-day "classics." Applications to a variety of scientific fields are showcased. Exercise sets are well crafted with the express intent of supporting pedagogy through recognition and repetition. R subroutines are employed as the software and graphics tool of choice. Brevity is a key component to the retention of the subject matter. The book presumes knowledge of linear algebra, probability, data analysis, and basic computer programming"--
ISBN: 9781118593370 (pdf)
LCCN: 2014015482Subjects--Topical Terms:
700459
Time-series analysis
--Data processing.
LC Class. No.: QA280
Dewey Class. No.: 001.4/2202855133
Basic data analysis for time series with R
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"This book emphasizes the collaborative analysis of data that is used to collect increments of time or space. Written at a readily accessible level, but with the necessary theory in mind, the author uses frequency- and time-domain and trigonometric regression as themes throughout the book. The content includes modern topics such as wavelets, Fourier series, and Akaike's Information Criterion (AIC), which is not typical of current-day "classics." Applications to a variety of scientific fields are showcased. Exercise sets are well crafted with the express intent of supporting pedagogy through recognition and repetition. R subroutines are employed as the software and graphics tool of choice. Brevity is a key component to the retention of the subject matter. The book presumes knowledge of linear algebra, probability, data analysis, and basic computer programming"--
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http://onlinelibrary.wiley.com/book/10.1002/9781118593233
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