Generalized Modified Inverse Weibull Distribution: Its Properties and Applications

Saboori, Hadi; Barmalzan, Ghobad; Ayat, Seyyed Masih

doi:10.1007/s13571-018-0182-1

Cited by 8 publications

(4 citation statements)

References 11 publications

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“…To be exact, the causalities between CO 2 emissions and economic growth were proven to be unidirectional [17,18] or bidirectional [15,17,19]. Furthermore, the unidirectional causality from energy consumption to CO 2 emissions was proven by Saboori B and Sulaiman J [14], Arouri, M E H et al [20], and Kasman A and Duman Y S [21], and the bidirectional causality between the two variables was also found by many scholars [15,17,22,23].…”

Section: Literature Reviewmentioning

confidence: 95%

“…The Environmental Kuznets curve proposed by Grossman and Krueger [12] is a helpful tool for exploring the relationship between carbon dioxide emissions and economic growth. Generally speaking, there exists a correlation between economic growth and CO 2 emissions, as suggested by Ozturk I [13], Saboori B [14], Shahbaz M [15], and Deviren S A [16]. To be exact, the causalities between CO 2 emissions and economic growth were proven to be unidirectional [17,18] or bidirectional [15,17,19].…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Carbon Dioxide Emissions, Economic Growth, and Selected Types of Fossil Energy Consumption in China: Empirical Evidence from 1965 to 2015

2017

Sustainability

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This paper empirically investigates the interactions among CO 2 emissions, economic growth, and three selected types of fossil energy consumption (coal, gas, and oil) using time series data from China over the period 1965-2015. Classic econometric analysis technologies including the Johansen cointegration test, the vector error correction model (VECM), and the Granger causality test based on VECM are employed to meet our objectives, and the presence of breaks in the data is also considered. Cointegration test result supports the existence of a long-run equilibrium relationship among the five variables, and the error correction mechanisms of the system involving the five variables are proven to be effective by VECM. Additionally, the Granger causality test based on VECM reveals that the bidirectional causalities between GDP and coal consumption, between GDP and gas consumption, and between coal consumption and CO 2 emissions and unidirectional causalities running from GDP and oil consumption to CO 2 emissions, from GDP to oil consumption, and from coal consumption to oil and gas consumption are found. Furthermore, several policy implications are proposed in the final section of this paper based on the empirical results.

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Section: Literature Reviewmentioning

confidence: 95%

Section: Literature Reviewmentioning

confidence: 99%

Carbon Dioxide Emissions, Economic Growth, and Selected Types of Fossil Energy Consumption in China: Empirical Evidence from 1965 to 2015

2017

Sustainability

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“…They are widely used in reliability and survival analyses [43][44][45]. Nowadays, many types of modifications, extensions, and variations of the model are used [46][47][48][49][50][51][52].…”

Section: Weibull Distributionmentioning

confidence: 99%

Influence of Disinfectants on Airport Conveyor Belts

et al. 2021

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The coronavirus disease has influenced almost all of our everyday activities. Traveling and transportation have been influenced significantly and there is no doubt that air transportation has been restricted and therefore reduced considerably. It is predicted that the change back to pre-pandemic conditions will take several years, and so it is a reasonable assumption that disinfectants will be used more frequently for a long time. The presented article initially deals with the possible impacts of the pandemic on aircraft infrastructure—namely, on the influence of disinfectants on the rubber materials used, for example, in conveyor belts. The proposed methodology is based on the Weibull analysis for conveyor belt lifetime prediction regarding the impact of disinfectants. The Weibull distribution is a continuous probability distribution that can be applied as a theoretical model for statistical data processing. It was named after Weibull, who suggested shape, scale, and location parameters that made the distribution meaningful and useful. Currently, this distribution is applied in many areas, such as biology, economics, and hydrology. In engineering applications, it can be used for reliability and survival analysis. It is used mainly in cases where failure time is dependent on the operating hours, cycles, or age of the component. In the reliability area, it can be used, for example, to predict the lifetime or failure time of a component. To show the consequences of material changes due to the use of disinfectants, this article also presents a CAE (Computer Aided Engineering) analysis that was used for the evaluation of other hyperelastic material characteristics. This research is based on the results of experimental measurements, during which the influence of the types of disinfectant commonly used for the elimination of the coronavirus disease on airport conveyor belt rubber segments was tested. From the performed analysis, it was found that the influence of disinfectants on the material characteristics, including material hardness, elasticity, and static and dynamic loading, could be significant. Therefore, the probability of mechanical damage to the rubber part of the conveyor belt becomes higher, and time intervals for the maintenance or repair of airport conveyor belts should be considered.

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“…Kang and Han [28] derived the approximate maximum likelihood estimators of parameters of an IWD under multiply type-II censoring and also proposed a simple graphical method for a goodness-of-fit test. Saboori et al [29] introduced a generalized modified inverse Weibull distribution, and some statistical and probabilistic properties were derived.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Estimations of Shannon Entropy and Rényi Entropy of Inverse Weibull Distribution

Ren

Han

2023

Mathematics

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In this paper, under the symmetric entropy and the scale squared error loss functions, we consider the maximum likelihood (ML) estimation and Bayesian estimation of the Shannon entropy and Rényi entropy of the two-parameter inverse Weibull distribution. In the ML estimation, the dichotomy is used to solve the likelihood equation. In addition, the approximation confidence interval is given by the Delta method. Because the form of estimation results is more complex in the Bayesian estimation, the Lindley approximation method is used to achieve the numerical calculation. Finally, Monte Carlo simulations and a real dataset are used to illustrate the results derived. By comparing the mean square error between the estimated value and the real value, it can be found that the performance of ML estimation of Shannon entropy is better than that of Bayesian estimation, and there is no significant difference between the performance of ML estimation of Rényi entropy and that of Bayesian estimation.

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Generalized Modified Inverse Weibull Distribution: Its Properties and Applications

Cited by 8 publications

References 11 publications

Carbon Dioxide Emissions, Economic Growth, and Selected Types of Fossil Energy Consumption in China: Empirical Evidence from 1965 to 2015

Carbon Dioxide Emissions, Economic Growth, and Selected Types of Fossil Energy Consumption in China: Empirical Evidence from 1965 to 2015

Influence of Disinfectants on Airport Conveyor Belts

Bayesian Estimations of Shannon Entropy and Rényi Entropy of Inverse Weibull Distribution

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