Socioeconomic Covariate-Dependent Bayesian Nonparametric Mixture Model for Household Spending Patterns to Identify Multidimensional Vulnerability

Household vulnerability assessment in Malaysia has traditionally relied on income-based indicators, which do not adequately capture multidimensional deprivation. To address this limitation, this study employs Random Tree–Dirichlet Process Mixture Model (RT-DPMM) to identify latent heterogeneity in s...

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Principais autores:	En Lee, Thian Song Ong, Yvonne Lee
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2026-05-01
Colecção:	Information
Assuntos:	socioeconomic characteristics household vulnerability household spending patterns clustering dirichlet process mixture model explainable machine learning
Acesso em linha:	https://www.mdpi.com/2078-2489/17/5/459
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