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Journals / Hacettepe Journal of Mathematics and Statistics / 2018 / Cilt: 47 - Sayı: 6

Slice sampler algorithm for generalized Pareto distribution

Mohammad ROSTAMİ
Mohd Bakri Adam YAHYA
Mohamed Hisham YAHYA
Noor Akma İBRAHİM
Pages
1690–1714
Publication Date
2022-10-18
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Finally, the slice sampler algorithm was employed to estimate the return and risk values of investment in Malaysian gold market.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model.
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Key Findings & Data:Two simulation studies have shown the performance of the peaks over given threshold (POT) and GPD density function on various simulated data sets.
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Conclusion & Impact:Finally, the slice sampler algorithm was employed to estimate the return and risk values of investment in Malaysian gold market.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Extreme value theory · Markov chain Monte Carlo · slice sampler

Abstract

In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. Two simulation studies have shown the performance of the peaks over given threshold (POT) and GPD density function on various simulated data sets. The results were compared with another commonly used Markov chain Monte Carlo (MCMC) technique called Metropolis-Hastings algorithm. Based on the results, the slice sampler algorithm provides closer posterior mean values and shorter $95\%$ quantile based credible intervals compared to the Metropolis-Hastings algorithm. Moreover, the slice sampler algorithm presents a higher level of stationarity in terms of the scale and shape parameters compared with the Metropolis-Hastings algorithm. Finally, the slice sampler algorithm was employed to estimate the return and risk values of investment in Malaysian gold market.

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Cite This Article

ROSTAMİ, M., YAHYA, M. B. A., YAHYA, M. H., İBRAHİM, N. A. (2022). Slice sampler algorithm for generalized Pareto distribution. Hacettepe Journal of Mathematics and Statistics, Cilt: 47 - Sayı: 6, 1690–1714. https://ajindex.com/articles/529848

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