Bayesian taut splines for estimating the number of modes

The number of modes in a probability density function is representative of the complexity of a model and can also be viewed as the number of subpopulations. Despite its relevance, there has been limited research in this area. A novel approach to estimating the number of modes in the univariate setti...

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Veröffentlicht in:	Computational statistics & data analysis 2024-08, Vol.196, p.107961, Article 107961
Hauptverfasser:	Chacón, José E., Fernández Serrano, Javier
Format:	Artikel
Sprache:	eng
Schlagworte:	Bayesian inference Bayesian theory case studies Compositional spline data analysis expert opinion Kernel density estimation Mode testing Model selection Number of modes prediction probability distribution
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