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The new half logistic-truncated exponential distribution (HL-TEXPD) offers a flexible statistical model. This distribution shows strong performance in engineering and medical data analysis.

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Area of Science:

  • Statistics
  • Probability Distributions

Background:

  • The "Half logistic" distribution, introduced by Balakrishnan (1991), is a well-established statistical model.
  • A modified version, the half logistic-truncated exponential distribution (HL-TEXPD), was developed by Gul and Mohsin in 2021.

Purpose of the Study:

  • To introduce and analyze the mathematical properties of the new half logistic-truncated exponential distribution (HL-TEXPD).
  • To assess the efficacy and applicability of the HL-TEXPD model using real-world data sets.

Main Methods:

  • Mathematical characterization of HL-TEXPD, including hazard function, Pth percentile, moment generating function, and Shannon entropy.
  • Simulation study to evaluate parameter estimation behavior.
  • Application of the HL-TEXPD model to three real data sets.
  • Total Time on Test (TTT) plot analysis to study failure rates.

Main Results:

  • The study characterized key mathematical properties of the HL-TEXPD.
  • Simulation results demonstrated the behavior of parameter estimates.
  • The HL-TEXPD model was successfully fitted to three diverse real data sets.
  • TTT plots provided insights into the failure rate characteristics of the data.

Conclusions:

  • The developed HL-TEXPD model exhibits favorable statistical properties.
  • The HL-TEXPD model proved effective and efficient for analyzing data in engineering and medical sciences.
  • The proposed distribution offers a viable alternative to classical and baseline models.