The four-parameter exponentiated Weibull model with Copula, properties and real data modeling.

Shehata, Wahid A. M.; Yousof, Haitham M.

doi:10.18187/pjsor.v17i3.3311

Cited by 21 publications

(3 citation statements)

References 41 publications

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“…• The CDF in (2) can be used for presenting a new discrete probability distribution for modeling the count data (see Aboraya et al [1], Ibrahim et al [30], Chesneau et al [17] and Yousof et al [60] for more details). • Many future works may be allocated to study these new bivariate Poisson Topp-Leone Burr XII distributions under some copulas (see Shehata and Yousof [50], Shehata and Yousof [51], Al-babtain et al [6], Shehata et al [53], Elgohari and Yousof [20], Elgohari and Yousof [21], Elgohari and Yousof [22], Elgohari et al [23] and Shehata et al [52]). • Some new acceptance sampling plans based on the Poisson Topp-Leone Burr XII distribution can be presented in separate article (see Ahmed and Yousof [4] and Ahmed et al [5]).…”

Section: Discussionmentioning

confidence: 99%

Modified Bagdonavicius-Nikulin Goodness-of-fit Test Statistic for the Compound Topp Leone Burr XII Model with Various Censored Applications

Khalil,

Aidi,

Ali

et al. 2024

Stat., optim. inf. comput.

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The Poisson Topp Leone Burr XII distribution is extensively studied due to its broad relevance in analyzing censored real datasets from engineering, economics, and medicine. In this research, the distribution's versatility is highlighted through the analysis of four specific real datasets. The study compares the Poisson Topp Leone Burr XII distribution with nine extensions of the Burr type XII distribution to determine which offers the best fit for these datasets. To evaluate the goodness-of-fit of the Poisson Topp Leone Burr XII distribution under right censoring, a modified Bagdonavi\v{c}ius-Nikulin goodness-of-fit test statistic is introduced and applied. This new test statistic is utilized to validate the distributional fit for the Poisson Topp Leone Burr XII distribution across the four right-censored datasets. The modified Bagdonavi\v{c}ius-Nikulin test statistic is employed to assess distributional validation, specifically in the context of right censoring. The application of this statistic involves analyzing each of the four censored datasets to confirm the appropriateness of the Poisson Topp Leone Burr XII distribution for these scenarios. Additionally, to support the evaluation of the modified goodness-of-fit test statistic, the Barzilai-Borwein algorithm is utilized. This algorithm is employed within a simulation study to further assess the effectiveness and reliability of the modified Bagdonavi\v{c}ius-Nikulin test statistic, thereby ensuring robust validation of the Poisson Topp Leone Burr XII distribution against the observed real datasets.

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Section: Discussionmentioning

confidence: 99%

Modified Bagdonavicius-Nikulin Goodness-of-fit Test Statistic for the Compound Topp Leone Burr XII Model with Various Censored Applications

Khalil,

Aidi,

Ali

et al. 2024

Stat., optim. inf. comput.

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“…The four datasets are given in the literature. More useful real data are available in Shehata et al, [47] and Shehata and Yousof ([44], [45], [46]).…”

Section: Applications Under Uncensored Samplesmentioning

confidence: 99%

The Poisson-Topp-Leone Burr Type-X II Model: Various Uncensored Applications for Statistical Modeling and Some Copulas

Abdullah,

Mohammed,

Farhana

2023

Stat., optim. inf. comput.

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The Poisson-Topp-Leone Burr type-X II distribution is studied mainly for illustrating its wide applicability under uncensored engineering and medical real-life datasets. The real-life datasets are checked and analyzed for the statistical modeling purpose. The Poisson-Topp-Leone Burr type-X II model is compared with other nine types of Burr type-X II extensions and provided the best results. For modeling the bivariate uncensored engineering and medical real-life datasets, we presented some bivariate version with some useful theoretical results. Those versions are investigated due to certain and common copulas.

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“…. Based on (13), when ε = 99% for a one-year time period, the interpretation is that there is only a very small chance (1%) that the insurance company will be bankrupted by an adverse outcome over the next year. Then, the VaRε(X) does not satisfy one of the four criteria for coherence.…”

Section: Var Indicatormentioning

confidence: 99%

Asymmetric Density for Risk Claim-Size Data: Prediction and Bimodal Data Applications

2021

Self Cite

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A new, flexible claim-size Chen density is derived for modeling asymmetric data (negative and positive) with different types of kurtosis (leptokurtic, mesokurtic and platykurtic). The new function is used for modeling bimodal asymmetric medical data, water resource bimodal asymmetric data and asymmetric negatively skewed insurance-claims payment triangle data. The new density accommodates the “symmetric”, “unimodal right skewed”, “unimodal left skewed”, “bimodal right skewed” and “bimodal left skewed” densities. The new hazard function can be “decreasing–constant–increasing (bathtub)”, “monotonically increasing”, “upside down constant–increasing”, “monotonically decreasing”, “J shape” and “upside down”. Four risk indicators are analyzed under insurance-claims payment triangle data using the proposed distribution. Since the insurance-claims data are a quarterly time series, we analyzed them using the autoregressive regression model AR(1). Future insurance-claims forecasting is very important for insurance companies to avoid uncertainty about big losses that may be produced from future claims.

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The four-parameter exponentiated Weibull model with Copula, properties and real data modeling.

Cited by 21 publications

References 41 publications

Modified Bagdonavicius-Nikulin Goodness-of-fit Test Statistic for the Compound Topp Leone Burr XII Model with Various Censored Applications

Modified Bagdonavicius-Nikulin Goodness-of-fit Test Statistic for the Compound Topp Leone Burr XII Model with Various Censored Applications

The Poisson-Topp-Leone Burr Type-X II Model: Various Uncensored Applications for Statistical Modeling and Some Copulas

Asymmetric Density for Risk Claim-Size Data: Prediction and Bimodal Data Applications

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