Basic Data Analysis for Time Series with R
-
Form:Einzelkauf Download
-
Sprache:Englisch
-
eBook Format:PDF
- ePUB 3 107,99 €
- PDF 107,99 € ausgewählt
107,99 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
Kopierschutz
Ja
Family Sharing
Nein
Text-to-Speech
Nein
Erscheinungsdatum
23.07.2014
Verlag
John Wiley & SonsSeitenzahl
320 (Printausgabe)
Dateigröße
14321 KB
Auflage
1. Auflage
Sprache
Englisch
EAN
9781118593370
Presents modern methods to analyzing data with multiple applications in a variety of scientific fields
Written at a readily accessible level, Basic Data Analysis for Time Series with R 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.
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, Basic Data Analysis for Time Series with R also features:
* Real-world examples to provide readers with practical hands-on experience
* Multiple R software subroutines employed with graphical displays
* Numerous exercise sets intended to support readers understanding of the core concepts
* Specific chapters devoted to the analysis of the Wolf sunspot number data and the Vostok ice core data sets
Written at a readily accessible level, Basic Data Analysis for Time Series with R 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.
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, Basic Data Analysis for Time Series with R also features:
* Real-world examples to provide readers with practical hands-on experience
* Multiple R software subroutines employed with graphical displays
* Numerous exercise sets intended to support readers understanding of the core concepts
* Specific chapters devoted to the analysis of the Wolf sunspot number data and the Vostok ice core data sets
Noch keine Bewertungen vorhanden
Verfassen Sie die erste Bewertung zu diesem Artikel
Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.
Kurze Frage zu unserer Seite
Vielen Dank für dein Feedback
Wir nutzen dein Feedback, um unsere Produktseiten zu verbessern. Bitte habe Verständnis, dass wir dir keine Rückmeldung geben können. Falls du Kontakt mit uns aufnehmen möchtest, kannst du dich aber gerne an unseren Kund*innenservice wenden.
zum Kundenservice