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Part 1: Document Description
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Citation |
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Title: |
4. Nurvita Trianasari, I Made Sumertajaya, Erfiani, I Wayan Mangku, Bivariate Beta Mixture Model with Correlations, sudah di publish pada Journal Communications in Mathematical Biology and Neuroscience (CMBN) (Q3 Scopus), Vol.2021, ID 26, tahun 2021. |
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Identification Number: |
doi:10.34820/FK2/34PIEQ |
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Distributor: |
Telkom University Dataverse |
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Date of Distribution: |
2023-10-05 |
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Version: |
1 |
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Bibliographic Citation: |
Trianasari, Nurvita, 2023, "4. Nurvita Trianasari, I Made Sumertajaya, Erfiani, I Wayan Mangku, Bivariate Beta Mixture Model with Correlations, sudah di publish pada Journal Communications in Mathematical Biology and Neuroscience (CMBN) (Q3 Scopus), Vol.2021, ID 26, tahun 2021.", https://doi.org/10.34820/FK2/34PIEQ, Telkom University Dataverse, V1 |
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Citation |
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Title: |
4. Nurvita Trianasari, I Made Sumertajaya, Erfiani, I Wayan Mangku, Bivariate Beta Mixture Model with Correlations, sudah di publish pada Journal Communications in Mathematical Biology and Neuroscience (CMBN) (Q3 Scopus), Vol.2021, ID 26, tahun 2021. |
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Identification Number: |
doi:10.34820/FK2/34PIEQ |
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Authoring Entity: |
Trianasari, Nurvita (telkom university) |
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Distributor: |
Telkom University Dataverse |
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Access Authority: |
Trianasari, Nurvita |
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Depositor: |
Trianasari, Nurvita |
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Date of Deposit: |
2022-09-22 |
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Study Scope |
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Keywords: |
Mathematical Sciences, Keywords: probabilistic clustering, MLE method, EM algorithm, ICL-BIC, Monte Carlo Simulation. |
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Abstract: |
The method of clustering is a probabilistic model based on clustering technique. The clustering method is often based on the assumption that data comes from a mixed model. One such mixture model is the beta mixed model. This mixed model can be used for the case of one variable or multiple variables. However, for the mixed beta model of the double variable, each variable is assumed to be independent. In this article, we propose a mixed beta model with correlated variables. The parameter estimation method uses the MLE method via the EM algorithm. While determining the optimal number of clusters using the ICL-BIC criteria. Monte Carlo simulation is used to see the performance of the model. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
CC0 Waiver |
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Other Study Description Materials |
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Label: |
DATAVERSE_NVT.xlsx |
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Notes: |
application/vnd.openxmlformats-officedocument.spreadsheetml.sheet |