A hierarchical study for urban statistical indicators on the prevalence of COVID-19 in Chinese city clusters based on multiple linear regression (MLR) and polynomial best subset regression (PBSR) analysis

Cheshmehzangi, A; Li, Y; Li, H; Zhang, S; Huang, X; Chen, X; Su, Z; Sedrez, Maycon; Dawodu, A

A hierarchical study for urban statistical indicators on the prevalence of COVID-19 in Chinese city clusters based on multiple linear regression (MLR) and polynomial best subset regression (PBSR) analysis

journal contribution

posted on 2024-06-06, 05:15 authored by A Cheshmehzangi, Y Li, H Li, S Zhang, X Huang, X Chen, Z Su, Maycon SedrezMaycon Sedrez, A Dawodu

A hierarchical study for urban statistical indicators on the prevalence of COVID-19 in Chinese city clusters based on multiple linear regression (MLR) and polynomial best subset regression (PBSR) analysis

History

Journal

Scientific Reports

Volume

12

Article number

1964

Pagination

1-16

Location

London, Eng.

ISSN

2045-2322

eISSN

2045-2322

Language

eng

Author URL

https://www.ncbi.nlm.nih.gov/pubmed/35121784

Publication classification

C1.1 Refereed article in a scholarly journal

Issue

1

Publisher

Nature Research

Usage metrics

Keywords

Uncategorised value

A hierarchical study for urban statistical indicators on the prevalence of COVID-19 in Chinese city clusters based on multiple linear regression (MLR) and polynomial best subset regression (PBSR) analysis

History

Journal

Volume

Article number

Pagination

Location

ISSN

eISSN

Language

Author URL

Publication classification

Issue

Publisher

Usage metrics

Categories

Keywords

Licence

Exports