A New Method  for Generating Continuous Distributions with Applications

In this paper, a new modifying method has been introduced by adding an extra parameter to generate a new family of distributions that has more flexibility and better model fitting. A special case has been considered; the exponential distribution. All the main properties of the new modified exponential distribution are derived, including the CDF, PDF, and quantile function. The maximum likelihood estimation method is used to estimate unknown parameters. The modified exponential distribution has been applied to two-lifetime data sets to illustrate its efficiency.

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Publication Details

Journal
European Journal of Pure and Applied Mathematics
Published
2025-05-01
DOI
https://doi.org/10.29020/nybg.ejpam.v18i2.5981
Primary Topic
Simulation Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

A New Method  for Generating Continuous Distributions with Applications

Mohammad A. Amleh, Morad Ahmad
European Journal of Pure and Applied Mathematics
Simulation Techniques and Applications
article

A New Method  for Generating Continuous Distributions with Applications

Mohammad A. Amleh, Morad Ahmad
article en

Abstract

In this paper, a new modifying method has been introduced by adding an extra parameter to generate a new family of distributions that has more flexibility and better model fitting. A special case has been considered; the exponential distribution. All the main properties of the new modified exponential distribution are derived, including the CDF, PDF, and quantile function. The maximum likelihood estimation method is used to estimate unknown parameters. The modified exponential distribution has been applied to two-lifetime data sets to illustrate its efficiency.

European Journal of Pure and Applied MathematicsVol. 18(2)
Zarqa University (JO)
University of Jordan, Zarqa University
Openalex Percentile: Top 90%
Simulation Techniques and Applications
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