Abstract:In this paper we study the distribution of order statistics of the inverse Pareto distribution. We consider the single and product moment of order statistics from inverse Pareto distribution. Also, we establish some recurrence relation for single moments of order statistics. The exact analytical expressions of entropy, residual entropy and past residual entropy for order statistics of inverse Pareto distribution is derived.
“…[ 28 ] discussed moments of dual generalized order statistics and characterization for the transmuted exponential model. [ 29 ] obtained order statistics of inverse Pareto distribution. The Lomax distribution has been used for reliability modeling and life testing (e.g., [ 30 ]), and applied to income and wealth distribution data ([ 31 , 32 ]), firm size ([ 33 ]), and queuing problems ([ 31 , 32 ]).…”
Section: Gull Alpha Power Lomax Distribution (Gapl)mentioning
The Gull Alpha Power Lomax distribution is a new extension of the Lomax distribution that we developed in this paper (GAPL). The proposed distribution’s appropriateness stems from its usefulness to model both monotonic and non-monotonic hazard rate functions, which are widely used in reliability engineering and survival analysis. In addition to their special cases, many statistical features were determined. The maximum likelihood method is used to estimate the model’s unknown parameters. Furthermore, the proposed distribution’s usefulness is demonstrated using two medical data sets dealing with COVID-19 patients’ mortality rates, as well as extensive simulated data applied to assess the performance of the estimators of the proposed distribution.
“…[ 28 ] discussed moments of dual generalized order statistics and characterization for the transmuted exponential model. [ 29 ] obtained order statistics of inverse Pareto distribution. The Lomax distribution has been used for reliability modeling and life testing (e.g., [ 30 ]), and applied to income and wealth distribution data ([ 31 , 32 ]), firm size ([ 33 ]), and queuing problems ([ 31 , 32 ]).…”
Section: Gull Alpha Power Lomax Distribution (Gapl)mentioning
The Gull Alpha Power Lomax distribution is a new extension of the Lomax distribution that we developed in this paper (GAPL). The proposed distribution’s appropriateness stems from its usefulness to model both monotonic and non-monotonic hazard rate functions, which are widely used in reliability engineering and survival analysis. In addition to their special cases, many statistical features were determined. The maximum likelihood method is used to estimate the model’s unknown parameters. Furthermore, the proposed distribution’s usefulness is demonstrated using two medical data sets dealing with COVID-19 patients’ mortality rates, as well as extensive simulated data applied to assess the performance of the estimators of the proposed distribution.
“…Several works in the literature have been done to improve the flexibility of the Burr XII distribution. The Marshall-Olkin exponentiated Burr XII distribution [2], the Marshall-Olkin Generalised Burr XII distribution [3], the Lindley-Burr XII distribution [4], the Kumaraswamy exponentiated Burr XII distribution [5], the Weibull Burr XII distribution [6], the Kumaraswamy Burr XII distribution [7], order statistics of inverse Pareto distribution [8], the exponentiated exponential Burr XII distribution [10], the Garhy-Burr XII [11], the equilibrium renewal Burr XII distribution [12], the Gompertz-modified Burr XII distribution [13], and the odd exponentiated half-logistic Burr XII distribution [14].…”
In this paper, we introduce a new four-parameter mixture distribution called the Harmonic Mixture Burr XII distribution. The proposed model can be used to model data which exhibit bimodal shapes or are heavy-tailed. Specific properties like non-central and incomplete moments, quantile function, entropy, mean and median deviation, mean residual life, moment generating function, and stressstrength reliability are derived. Maximum likelihood estimation, ordinary least squares estimation, weighted least squares estimation, Cramér-von Mises estimation, and Anderson-Darling estimation methods were used to estimate the parameters of the distribution. Simulation studies was performed to assess the estimators and the maximum likelihood estimation was adjudged the best estimator. Using three sets of lifetime data, the empirical importance of the new distribution was determined. When compared to nine (9) extensions of the Burr XII distribution, it was clear that the proposed distribution fit the data better. Using the proposed model, a log-linear regression model called the log-harmonic mixture Burr XII is proposed.
<abstract><p>We proposed in this article a new three-parameter distribution, which is referred as the Topp-Leone exponentiated exponential model is proposed. It is used in modeling claim and risk data applied in actuarial and insurance studies. The probability density function of the suggested distribution can be unimodel and positively skewed. Different distributional and mathematical properties of the TL-EE model were provided. Furthermore, we established a maximum likelihood estimation method for estimating the unknown parameters involved in the model, and some actuarial measures were calculated. Also, the potential of these actuarial statistics were provided via numerical simulation experiments. Finally, two real datasets of insurance losses were analyzed to prove the performance and superiority of the suggested model among all its competitors distributions.</p></abstract>
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