Bayesian nonparametric model for weighted data using mixture of Burr XII distributions Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.59139/stattrans-2025-038
In this paper, we develop a Bayesian nonparametric approach for analyzing weighted survival data. Specifically, we employ the Dirichlet Process Burr XII Mixture Model (DPBMM) to estimate the underlying density and survival functions when the observed data are weighted. Parameters are inferred using Markov chain Monte Carlo (MCMC) methods, and the Metropolis- Hastings algorithm is applied to obtain de-biased samples from the weighted observations. Numerical illustrations are provided using both simulated and real lifetime data, including the presence of censored observations. The performance of the proposed method is compared with classical kernel density estimates to demonstrate its flexibility in modeling complex and heavy-tailed distributions.
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- article
- Landing Page
- https://doi.org/10.59139/stattrans-2025-038
- http://sit.stat.gov.pl/SiT/2025/4/gus_sit_2025_04_soleiman_khazaei_soghra_bohlourihajjar_bayesian_nonparametric_model.pdf
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- diamond
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- https://openalex.org/W7110181032
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https://openalex.org/W7110181032Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.59139/stattrans-2025-038Digital Object Identifier
- Title
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Bayesian nonparametric model for weighted data using mixture of Burr XII distributionsWork title
- Type
-
articleOpenAlex work type
- Publication year
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2025Year of publication
- Publication date
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2025-12-05Full publication date if available
- Authors
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Soleiman Khazaei, Soghra BohlourihajjarList of authors in order
- Landing page
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https://doi.org/10.59139/stattrans-2025-038Publisher landing page
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https://sit.stat.gov.pl/SiT/2025/4/gus_sit_2025_04_soleiman_khazaei_soghra_bohlourihajjar_bayesian_nonparametric_model.pdfDirect link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://sit.stat.gov.pl/SiT/2025/4/gus_sit_2025_04_soleiman_khazaei_soghra_bohlourihajjar_bayesian_nonparametric_model.pdfDirect OA link when available
- Concepts
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Dirichlet process, Markov chain Monte Carlo, Mathematics, Nonparametric statistics, Bayesian probability, Dirichlet distribution, Kernel (algebra), Metropolis–Hastings algorithm, Markov chain, Kernel density estimation, Algorithm, Monte Carlo method, Statistics, Applied mathematics, Mixture model, Gibbs sampling, Bayesian inference, Hierarchical Dirichlet process, Kernel method, Computer science, Probability density function, Kernel smoother, Flexibility (engineering)Top concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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