A Copula Discretization of Time Series-Type Model for Examining Climate Data-Reference-Cited by-同舟云学术

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A Copula Discretization of Time Series-Type Model for Examining Climate Data

Published:2024-08-03 Issue:15 Volume:12 Page:2419
ISSN:2227-7390
Container-title:Mathematics
language:en
Short-container-title:Mathematics

Author:

Fernando Dimuthu¹,Atutey Olivia²,Diawara Norou³^ORCID

Affiliation:

1. Department of Statistical Sciences, Wake Forest University, Winston-Salem, NC 27106, USA

2. Department of Mathematics and Statistics, University of South Alabama, Mobile, AL 36688, USA

3. Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA 23529, USA

Abstract

The study presents a comparative analysis of climate data under two scenarios: a Gaussian copula marginal regression model for count time series data and a copula-based bivariate count time series model. These models, built after comprehensive simulations, offer adaptable autocorrelation structures considering the daily average temperature and humidity data observed at a regional airport in Mobile, AL.

Publisher

MDPI AG

Link

https://www.mdpi.com/2227-7390/12/15/2419/pdf

Reference20 articles.

1. Chaudhari, P., Rana, D.P., Mehta, R.G., Mistry, N.J., and Raghuwanshi, M.M. (2014). Discretization of temporal data: A survey. arXiv.

2. A multi-breakpoints approach for symbolic discretization of time series;Graff;Knowl. Inf. Syst.,2020

3. TA4L: Efficient temporal abstraction of multivariate time series;Mordvanyuk;Knowl.-Based Syst.,2022

4. Bivariate colour maps for visualizing climate data;Teuling;Int. J. Climatol.,2011

5. A regional perspective on trends in continental evaporation;Teuling;Geophys. Res. Lett.,2009

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