Derryberry Basic Data Analysis for Time Series with R

1. Auflage 2014
ISBN: 978-1-118-59337-0
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 320 Seiten, E-Book

Written at a readily accessible level, Basic Data Analysisfor Time Series with R emphasizes the mathematical importanceof collaborative analysis of data used to collect increments oftime or space. Balancing a theoretical and practical approach toanalyzing data within the context of serial correlation, the bookpresents a coherent and systematic regression-based approach tomodel selection. The book illustrates these principles ofmodel selection and model building through the use of informationcriteria, cross validation, hypothesis tests, and confidenceintervals.
Focusing on frequency- and time-domain and trigonometricregression as the primary themes, the book also includes moderntopical coverage on Fourier series and Akaike's InformationCriterion (AIC). In addition, Basic Data Analysis for TimeSeries with R also features:
* Real-world examples to provide readers with practical hands-onexperience
* Multiple R software subroutines employed with graphicaldisplays
* Numerous exercise sets intended to support readersunderstanding of the core concepts
* Specific chapters devoted to the analysis of the Wolf sunspotnumber data and the Vostok ice core data sets

Autoren/Hrsg.

Derryberry, DeWayne R.

Über Autor(innen)

DeWayne R. Derryberry, PhD, is Associate Professor in the Department of Mathematics and Statistics at Idaho State University. Dr. Derryberry has published more than a dozen journal articles and his research interests include meta-analysis, discriminant analysis with messy data, time series analysis of the relationship between several cancers, and geographically-weighted regression.