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A Multilevel Nonparametric Bayesian Model
Un Modelo Bayesiano No Paramétrico Multinivel
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https://doi.org/10.15446/rce.v48n3.122305Keywords:
Nonparametric Bayesian model, Dirichlet process, Chinese Restaurant Process, Clustering, Linear regression. (en)Modelo Bayesiano no paramétrico, Proceso de Dirichlet, Proceso del Restaurante Chino, Agrupamiento, Regresión lineal. (es)
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This work presents the development of a multilevel Bayesian nonparametric model that allows for the estimation of linear relationships in heterogeneous data sets, while simultaneously identifying clusters without the need to specify the number of groups in advance. The study includes the mathematical development of the model using the Chinese Restaurant Process and the implementation of algorithms for its fitting. The results obtained from real data show that the model performs well in both clustering data and characterizing linear relationships, achieving results comparable and even better to those obtained by traditional parametric methods.
Este trabajo presenta el desarrollo de un modelo Bayesiano no paramétrico multinivel diseñado para estimar relaciones lineales en conjuntos de datos heterogéneos, mientras identifica simultáneamente conglomerados sin requerir la especificación previa del número de grupos. El estudio incluye la formulación matemática del modelo utilizando el Proceso del Restaurante Chino, así como la implementación de algoritmos para su ajuste. Los resultados obtenidos con datos reales muestran que el modelo tiene un buen desempeño tanto en la agrupación de los datos como en la caracterización de las relaciones lineales, alcanzando resultados comparables e incluso superiores a los obtenidos mediante métodos paramétricos tradicionales.
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