Non-Gaussian Autoregressive-Type Time Series (PDF)
58 DeutschlandCard Punkte sammeln
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenloser tolino webreader
This book brings together a variety of non-Gaussian autoregressive-type models to analyze time-series data. This book collects and collates most of the available models in the field and provide their probabilistic and inferential properties. This book classifies the stationary time-series models into different groups such as linear stationary models with non-Gaussian innovations, linear stationary models with non-Gaussian marginal distributions, product autoregressive models and minification models. Even though several non-Gaussian time-series models are available in the literature, most of them are focusing on the model structure and the probabilistic properties.
As researcher in time-series analysis, Prof. Balakrishna received the UK-India Education and Research Initiative Fellowship, in 2007, to continue the research collaboration at University of Warwick. Earlier, he also received the Commonwealth Post-Doctoral Fellowship in 1999-2000 to do research at the University of Birmingham, UK. He was awarded the Distinguished Statistician Award by the Indian Society for Probability and Statistics, in 2018. Professor Balakrishna has published 55 research papers in refereed journals and successfully guided 10 scholars for their Ph.D. degree. Professor Balakrishna has visited several universities of the world: the University of Waterloo, Canada, to continue his ongoing research collaboration in time series; a visiting scientist at Technical University Dresden, Germany, during 2003-2004; and a visiting professor at Michigan State University, USA, during 2015-2016. He has attended several national and international conferences in India as well as abroad.
- Autor: N. Balakrishna
- 2022, 1st ed. 2021, 225 Seiten, Englisch
- Verlag: Springer Nature Singapore
- ISBN-10: 9811681627
- ISBN-13: 9789811681622
- Erscheinungsdatum: 27.01.2022
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 2.99 MB
- Ohne Kopierschutz
- Vorlesefunktion
Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
---|
Schreiben Sie einen Kommentar zu "Non-Gaussian Autoregressive-Type Time Series".
Kommentar verfassen