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Inferential Survival Analysis for Type II Censored Truncated Exponential Topp Leone Exponential Distribution with Application to Engineering Data |
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PP: 3095-3120 |
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doi:10.18576/isl/120736
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Author(s) |
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Samia A. Salem,
Osama E. Abo-Kasem,
Rania M. Agwa,
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Abstract |
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| This study focuses on estimating the unknown parameters of the truncated exponential Topp-Leon distribution using a type II scheme. We estimate the unknown parameters, survival, and hazard functions using maximum likelihood estimation methods. Additionally, we derive the approximate variance covariance matrix and asymptotic confidence intervals. Furthermore, we compute Bayesian estimates of the unknown parameters under squared error and linear loss functions. To generate samples from the posterior density functions, we use the Metropolies-Hastings algorithm. We demonstrate the effectiveness of the proposed distribution by applying it to two data sets: Monte Carlo simulation and real data set. Our results show that the proposed distribution provides accurate estimates of the unknown parameters and performs well in fitting the data. Our findings also indicate that Bayesian estimation can provide more precise estimates with narrower confidence intervals compared to maximum likelihood estimation method. In summary, the study provides a comprehensive analysis of the estimation of the unknown parameters for the truncated exponential Topp-Leone distribution using a type II scheme. Also, the results demonstrate the potential of this distribution in modeling real data and the usefulness of both maximum likelihood and Bayesian estimation methods in obtaining accurate parameter estimates.
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