Basic Data Analysis for Time Series with R
von DeWayne R. DerryberryWritten 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
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
