| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0646627 |
| utime |
20260226093010.7 |
| mtime |
20260226235959.9 |
| title
(primary) (eng) |
Statistical Analysis of the 2024 U.S. Presidential Election: Demographics and Swing States |
| specification |
| page_count |
10 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0645858 |
| ISBN |
978-80-245-2571-6 |
| title
|
RELIK 2025 Conference Proceedings |
| page_num |
181-190 |
| publisher |
| place |
Prague |
| name |
University of Economics and Business |
| year |
2025 |
|
| editor |
|
|
| keyword |
election results |
| keyword |
linear regression |
| keyword |
robust statistics |
| keyword |
regularization |
| keyword |
electoral demography |
| author
(primary) |
| ARLID |
cav_un_auth*0345793 |
| name1 |
Kalina |
| name2 |
Jan |
| institution |
UTIA-B |
| full_dept (cz) |
Stochastická informatika |
| full_dept (eng) |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department (eng) |
SI |
| full_dept |
Department of Stochastic Informatics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GA24-10078S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0472835 |
|
| abstract
(eng) |
This paper provides an analysis of the 2024 U.S. presidential election using advanced statistical techniques. The study models the popular vote as a response to eight demographic predictors at the state-wide level, incorporating results from the 2020 election to enhance the analysis. A particular focus is given to the application of two recently developed tools inspired by the least weighted squares estimator (LWS): LWS-lasso estimator and LWSquantiles, which are robust methods designed to handle datasets under multicollinearity, heteroscedasticity, and the presence of outliers. The findings emphasize the critical influence of demographic factors in shaping electoral outcomes, illustrating how demographic shifts impact the dynamics of the 2024 election. Special attention is given to the results in seven key swing states, offering precise insights into their pivotal roles in the electoral landscape. Based on the analysis, we propose a novel classification of the swing states into three distinct clusters, taking into account both their demographic outlyingness and their role in the linear model, offering new insights into their strategic importance in the electoral process. |
| action |
| ARLID |
cav_un_auth*0503454 |
| name |
RELIK 2025: The International Scientific Conference. Reproduction of Human Capital - mutual links and connections /18./ |
| dates |
20251113 |
| mrcbC20-s |
20251114 |
| place |
Prague |
| url |
https://relik.vse.cz/conference |
| country |
CZ |
|
| RIV |
BB |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10103 |
| reportyear |
2026 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0376315 |
| confidential |
S |
| arlyear |
2025 |
| mrcbU14 |
SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU63 |
cav_un_epca*0645858 RELIK 2025 Conference Proceedings 978-80-245-2571-6 181 190 Prague University of Economics and Business 2025 |
| mrcbU67 |
Langhamrová J. 340 |
| mrcbU67 |
Vrabcová J. 340 |
|