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<p>In this study, we propose a novel generalization of the exponential model through a distorted transformation. The distortion function, we have used is parsimonious and hence no new parameters are introduced to the baseline exponential model. Various distributional and structural properties are explored. Important reliability characteristics are derived and developed characterization results. Parameter estimation was performed using maximum likelihood estimation, Cramer–von Mises estimation, Anderson–Darling estimation, and weighted least squares. Inference procedures are developed for both censored and uncensored setups, and the performance of the estimator has been examined in detail through an extensive simulation study. Finally, the practical importance of the proposed model has been illustrated with the help of two real data sets.</p>

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A New Distorted Generalization of the Exponential Model with its Reliability Properties and Applications

  • 期刊论文

  • 发表日期：

    2026年7月29日

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  • Jabir Bengalath,
  • Dileepkumar M,
  • Bindu Punathumparambath

摘要

In this study, we propose a novel generalization of the exponential model through a distorted transformation. The distortion function, we have used is parsimonious and hence no new parameters are introduced to the baseline exponential model. Various distributional and structural properties are explored. Important reliability characteristics are derived and developed characterization results. Parameter estimation was performed using maximum likelihood estimation, Cramer–von Mises estimation, Anderson–Darling estimation, and weighted least squares. Inference procedures are developed for both censored and uncensored setups, and the performance of the estimator has been examined in detail through an extensive simulation study. Finally, the practical importance of the proposed model has been illustrated with the help of two real data sets.