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  • Open Access


    Sine Power Lindley Distribution with Applications

    Abdullah M. Almarashi*

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 373-386, 2022, DOI:10.32604/iasc.2022.018043

    Abstract Sine power Lindley distribution (SPLi), a new distribution with two parameters that extends the Lindley model, is introduced and studied in this paper. The SPLi distribution is more flexible than the power Lindley distribution, and we show that in the application part. The statistical properties of the proposed distribution are calculated, including the quantile function, moments, moment generating function, upper incomplete moment, and lower incomplete moment. Meanwhile, some numerical values of the mean, variance, skewness, and kurtosis of the SPLi distribution are obtained. Besides, the SPLi distribution is evaluated by different measures of entropy such More >

  • Open Access


    Inference of Truncated Lomax Inverse Lomax Distribution with Applications

    Abdullah Ali H. Ahmadini1, Amal Hassan2, M. Elgarhy3,*, Mahmoud Elsehetry4, Shokrya S. Alshqaq5, Said G. Nassr6

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 199-212, 2021, DOI:10.32604/iasc.2021.017890

    Abstract This paper introduces a modified form of the inverse Lomax distribution which offers more flexibility for modeling lifetime data. The new three-parameter model is provided as a member of the truncated Lomax-G procedure. The new modified distribution is called the truncated Lomax inverse Lomax distribution. The density of the new model can be represented as a linear combination of the inverse Lomax distribution. Expansions for quantile function, moment generating function, probability weighted moments, ordinary moments, incomplete moments, inverse moments, conditional moments, and Rényi entropy measure are investigated. The new distribution is capable of monotonically increasing,… More >

  • Open Access


    A Combined Sensitive Matrix Method and Maximum Likelihood Method for Uncertainty Inverse Problems

    W. Zhang1, X. Han1,2, J. Liu1, Z. H. Tan1

    CMC-Computers, Materials & Continua, Vol.26, No.3, pp. 201-226, 2011, DOI:10.3970/cmc.2011.026.201

    Abstract The uncertainty inverse problems with insufficiency and imprecision in the input and/or output parameters are widely existing and unsolved in the practical engineering. The insufficiency refers to the partly known parameters in the input and/or output, and the imprecision refers to the measurement errors of these ones. In this paper, a combined method is proposed to deal with such problems. In this method, the imprecision of these known parameters can be described by probability distribution with a certain mean value and variance. Sensitive matrix method is first used to transform the insufficient formulation in the More >

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