arXiv subjects

Lazhar Benkhelifa

Publications and source records attributed to Lazhar Benkhelifa.

6 recordsLinked to original sources

arXiv2026

Modi linear failure rate distribution with application to survival time data

A new lifetime model, named the Modi linear failure rate distribution, is suggested. This flexible model is capable of accommodating a wide range of hazard rate shapes, including decreasing, increasing, bathtub, upside-down bathtub, and modified bathtub forms, making it particularly suitable for modeling diverse survival and reliability data. Our proposed model contains the Modi exponential distribution and the Modi Rayleigh distribution as sub-models. Numerous mathematical and reliability properties are derived, including the $r^{th}$ moment, moment generating function, $r^{th}$ conditional moment, quantile function, order statistics, mean deviations, Rényi entropy, and reliability function. The method of maximum likelihood is employed to estimate the model parameters. Monte Carlo simulations are presented to examine how these estimators perform. The superior fit of our newly introduced model is proved through two real-world survival data sets.

stat.ME↗

arXiv2025

Power new generalized class of Kavya-Manoharan distributions with an application to exponential distribution

Recently, Verma et al. (2025) introduced a novel generalized class of Kavya-Manoharan distributions, which have demonstrated significant utility in reliability analysis and the modeling of lifetime data. This paper proposes an extension of this class by applying the power generalization technique, thereby enhancing more flexibility and applicability. We take the exponential distribution as the baseline distribution to introduce a new model capable of accommodating both monotonic and non-monotonic hazard rate functions. Our model includes eleven submodels. We present several statistical properties of the introduced model, including moments, generating and characteristic functions, mean deviations, quantile function, mean residual life function, Rényi entropy, order statistics, and reliability. To estimate the unknown model parameters, we use the maximum likelihood approach. A simulation study is conducted to assess the validity of the maximum likelihood estimator. The superiority of the new distribution is demonstrated through the use of a real data application.

stat.ME↗

arXiv2017

Log-Lindley generated family of distributions

A new generator of univariate continuous distributions, with two additional parameters, called the Log-Lindley generated family is introduced. Some special distributions in the new family are presented. Some mathematical properties of the new family are studied. The maximum likelihood method to estimate model parameters is employed. The potentiality of the new generator is illustrated using a real data set.

stat.ME↗

arXiv2017

Efficient estimation in the Topp-Leone distribution

In the current paper, the estimation of the probability density function and the cumulative distribution function of the Topp-Leone distribution is considered. We derive the following estimators: maximum likelihood estimator, uniformly minimum variance unbiased estimator, percentile estimator, least squares estimator and weighted least squares estimator. A simulation study shows that the maximum likelihood estimator is more efficient than the others estimators.

stat.ME↗

arXiv2016

The Weibull Birnbaum-Saunders Distribution: Properties and Applications

This paper introduces a new four-parameter lifetime model called the Weibull Birnbaum-Saunders distribution. This new distribution represents a more flexible model for the lifetime data. Its failure rate function can be increasing, decreasing, upside-down bathtub shaped, bathtub-shaped or modified bathtub shaped depending on its parameters. Some structural properties of the proposed model are investigated including expansions for the cumulative and density functions, moments, generating function, mean deviations, order statistics and reliability. The maximum likelihood estimation method is used to estimate the model parameters and the observed information matrix is determined. The flexibility of the new model is shown by means of two real data sets.

stat.AP↗

arXiv2016

The Marshall-Olkin extended generalized Gompertz distribution

A new four-parameter model called the Marshall-Olkin extended generalized Gompertz distribution is introduced. Its hazard rate function can be constant, increasing, decreasing, upside-down bathtub or bathtub-shaped depending on its parameters. Some mathematical properties of this model such as expansion for the density function, moments, moment generating function, quantile function, mean deviations, mean residual life, order statistics and Rényi entropy are derived. The maximum likelihood technique is used to estimate the unknown model parameters and the observed information matrix is determined. The applicability of the proposed model is shown by means of a real data set.

math.ST↗