Bayesian Multilevel Models for Repeated Measures Data (ePub)
A Conceptual and Practical Introduction in R
(Sprache: Englisch)
This comprehensive book is an introduction to multilevel Bayesian models in R using brms and the Stan programming language. Featuring a series of fully worked analyses of repeated-measures data, focus is placed on active learning through the analyses of the...
sofort als Download lieferbar
eBook (ePub)
68.90 €
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenloser tolino webreader
Produktdetails
Produktinformationen zu „Bayesian Multilevel Models for Repeated Measures Data (ePub)“
This comprehensive book is an introduction to multilevel Bayesian models in R using brms and the Stan programming language. Featuring a series of fully worked analyses of repeated-measures data, focus is placed on active learning through the analyses of the progressively more complicated models presented throughout the book.
Autoren-Porträt von Santiago Barreda, Noah Silbert
Santiago Barreda is a phonetician in the Linguistics Department at the University of California, Davis, USA, with a particular interest in speech perception. Noah Silbert is a former Academic and is currently a practicing Stoic. His training and background are in phonetics, perceptual modeling, and statistics.
Bibliographische Angaben
- Autoren: Santiago Barreda , Noah Silbert
- 2023, 1. Auflage, 484 Seiten, Englisch
- Verlag: Taylor & Francis
- ISBN-10: 1000869830
- ISBN-13: 9781000869835
- Erscheinungsdatum: 18.05.2023
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: ePub
- Größe: 13 MB
- Ohne Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
Kommentar zu "Bayesian Multilevel Models for Repeated Measures Data"
Schreiben Sie einen Kommentar zu "Bayesian Multilevel Models for Repeated Measures Data".
Kommentar verfassen