Basic Data Analysis for Time Series with R
DeWayne R. Derryberry
Wiley
<p>Written at a readily accessible level, <i>Basic Data Analysis for Time Series with R</i> emphasizes the mathematical importance of collaborative analysis of data used to collect increments of time or space. Balancing a theoretical and practical approach to analyzing data within the context of serial correlation, the book presents a coherent and systematic regression-based approach to model selection.  The book illustrates these principles of model selection and model building through the use of information criteria, cross validation, hypothesis tests, and confidence intervals.</p> <p>Focusing on frequency- and time-domain and trigonometric regression as the primary themes, the book also includes modern topical coverage on Fourier series and Akaike's Information Criterion (AIC). In addition, <i>Basic Data Analysis for Time Series with R</i> also features:</p> <ul> <li>Real-world examples to provide readers with practical hands-on experience</li> <li>Multiple R software subroutines employed with graphical displays</li> <li>Numerous exercise sets intended to support readers understanding of the core concepts</li> <li>Specific chapters devoted to the analysis of the Wolf sunspot number data and the Vostok ice core data sets</li> </ul>