Mejora de la visualización de gráficos PRINCALS en R: Un estudio de caso sobre "La Violencia contra la Mujer durante el 2018"
Violence against women is a global public health issue. In Peru, the number of reported cases continues to rise, and studies addressing this problem often involve a wide variety of qualitative variables. The aim of this study is to optimize the quality of the graphs generated through categorical pri...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | Perú |
| Institución: | Universidad Nacional Mayor de San Marcos |
| Repositorio: | Revistas - Universidad Nacional Mayor de San Marcos |
| Idioma: | español |
| OAI Identifier: | oai:revistasinvestigacion.unmsm.edu.pe:article/30103 |
| Acceso en línea: | https://revistasinvestigacion.unmsm.edu.pe/index.php/matema/article/view/30103 |
| Access Level: | acceso abierto |
| Palabra clave: | Principal Component Analysis Optimal Scaling Violence Against Women Gifi g.princals Análisis de componentes principales escalamiento óptimo violencia contra la mujer |
| Sumario: | Violence against women is a global public health issue. In Peru, the number of reported cases continues to rise, and studies addressing this problem often involve a wide variety of qualitative variables. The aim of this study is to optimize the quality of the graphs generated through categorical principal component analysis (PRINCALS) using the R programming language, focusing on cases of economic and other types of violence during the year 2018. The text outlines the foundations of the PRINCALS method and highlights the advantages of optimal scaling for transforming qualitative variables into quantitative ones, enabling a deeper analysis of categorical data. Finally, the graphs produced using the Gifi package are compared to those generated with g.princals, demonstrating signi_cant improvements in visual clarity, axis alignment, and reduction of label overlap. |
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