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Bayesian estimation for median discrete Weibull regression model

Monthira Duangsaphon Sukit Sokampang Kannat Na Bangchang

Abstrak

<abstract><p>The discrete Weibull model can be adapted to capture different levels of dispersion in the count data. This paper takes into account the direct relationship between explanatory variables and the median of discrete Weibull response variable. Additionally, it provides the Bayesian estimate of the discrete Weibull regression model using the random walk Metropolis algorithm. The prior distributions of the coefficient predictors were carried out based on the uniform non-informative, normal and Laplace distributions. The performance of the Bayes estimators was also compared with the maximum likelihood estimator in terms of the mean square error and the coverage probability through the Monte Carlo simulation study. Meanwhile, a real data set was analyzed to show how the proposed model and the methods work in practice.</p></abstract>

Penulis (3)

M

Monthira Duangsaphon

S

Sukit Sokampang

K

Kannat Na Bangchang

Format Sitasi

Duangsaphon, M., Sokampang, S., Bangchang, K.N. (2024). Bayesian estimation for median discrete Weibull regression model. https://doi.org/10.3934/math.2024016

Akses Cepat

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Informasi Jurnal
Tahun Terbit
2024
Bahasa
en
Total Sitasi
Sumber Database
CrossRef
DOI
10.3934/math.2024016
Akses
Terbatas