Your browser doesn't support javascript.
Functional, Multivariate Functional and Spatial PCA: Application to Covid-19 Data in the African Continent
12th International Conference on Information Systems and Advanced Technologies, ICISAT 2022 ; 624 LNNS:318-328, 2023.
Article in English | Scopus | ID: covidwho-2281342
ABSTRACT
Covid-19 pandemic has negatively impacted many areas, including the economy and health care facilities, and has left more than 5 million deaths worldwide. In this paper, we use functional data analysis methods to describe evolution of the number of cases and the number of deaths of Covid-19 in Africa. We perform functional principal component analysis, Multivariate functional component analysis and spatial component analysis to characterize better the phenomena and spatial data to determine the impact of a region's neighborhood on number of cases. The obtained results allow us to have a better knowledge of the evolution of the pandemic in African continent. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Keywords

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 12th International Conference on Information Systems and Advanced Technologies, ICISAT 2022 Year: 2023 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 12th International Conference on Information Systems and Advanced Technologies, ICISAT 2022 Year: 2023 Document Type: Article