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This is a Observational study (also classified as: In Vitro Study).

August 19, 2025Deleted JournalOpen Access

A new probability Chen model: Properties, risk analysis and distributions validation for testing using the right censored real data

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The BXGZC model improves fitting for right-censored data, outperforming traditional chen distribution methods.
Key indicators like value-at-risk and tail-value-at-risk show enhanced accuracy, particularly with real data.
Using simulation studies and various estimation techniques, the model's performance was rigorously evaluated across domains.
The modified goodness-of-fit test confirms the BXGZC model's utility in actuarial evaluations for extreme loss modeling.

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The proposed BXGZC model enhances risk analysis by improving distribution fitting in right censored datasets, indicating greater adaptability.

Ibrahim et al. (2025) studied this question.

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The proposed BXGZC model enhances risk analysis by improving distribution fitting in right censored datasets, indicating greater adaptability.