Bayesian Inference for Finite Mixture Regression Model Based on Non-Iterative Algorithm
نویسندگان
چکیده
Finite mixtures normal regression (FMNR) models are widely used to investigate the relationship between a response variable and set of explanatory variables from several unknown latent homogeneous groups. However, classical EM algorithm Gibbs sampling deal with this model have weak points. In paper, non-iterative for fitting FMNR is proposed Bayesian perspective. The procedure can generate independently identically distributed samples posterior distributions parameters produce more reliable estimations than sampling. Simulation studies conducted illustrate performance supporting results. Finally, real data analyzed show usefulness methodology.
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ژورنال
عنوان ژورنال: Mathematics
سال: 2021
ISSN: ['2227-7390']
DOI: https://doi.org/10.3390/math9060590