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C₁, C₂, C₃, C₄, í µí°´ µí°´ * , í µí° ¶ * , K.S. and (p-value) for the relief times data. Models C₁, C₂, C₃, C₄ í µí°´ µí°´ * , í µí° ¶ * K.S. (p-value)
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In this article, we introduce a new distribution called the McDonald Erlangtruncated exponential distribution. Various structural properties including explicit expressions for the moments, moment generating function, mean deviation of the new distribution are derived. The estimation of the model parameters is performed by maximum likelihood method....
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... 3 gives the KDE plots (see Rosenblat (1956) and Parzen (1962) The data represents the lifetime data relating to relief times (in minutes) of patients receiving an analgesic (see Gross and Clark (1975) First data set Second data set Tables 2 and 4 gives the MLEs and SEsvalues for the two data sets. Table 3 Table 5: C₁, C₂, C₃, C₄, í µí°´ µí°´ * , í µí° ¶ * , K.S. and (p-value) for the survival times data. Models C₁, C₂, C₃, C₄ í µí°´ µí°´ * , í µí° ¶ * From Table 3 and 5 we conclude that the proposed lifetime McETEx model is much better than the Ex, MomEx, MOEx, GMOEx, KEx, BEx, MOKEx and KMOEx models so the new lifetime model is a good alternative to these models in modeling relief times and survival times data sets. ...Context 2
... 3 Table 5: C₁, C₂, C₃, C₄, í µí°´ µí°´ * , í µí° ¶ * , K.S. and (p-value) for the survival times data. Models C₁, C₂, C₃, C₄ í µí°´ µí°´ * , í µí° ¶ * From Table 3 and 5 we conclude that the proposed lifetime McETEx model is much better than the Ex, MomEx, MOEx, GMOEx, KEx, BEx, MOKEx and KMOEx models so the new lifetime model is a good alternative to these models in modeling relief times and survival times data sets. ...Similar publications
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Citations
... Ali et al. (2020) [1] introduced a new discrete Time Between Events control chart following discrete Weibull distribution, by derived the design of the proposed chart analytically and discussed numerically. Elbatal and Aldukeel (2021) [2] discussed the McDonald Erlang-truncated exponential distribution with three shape parameters. Sayyed et al. (2021) [15] studied the effect of inspection error on cumulative sum (CUSUM) control charts for controlling the parameters of a random variable under Erlang-truncated exponential distribution, also derived expression for the parameter of the CUSUM chart. ...
In this paper, the discrete Erlang-truncated exponential distribution is defined by using the general approach of discretizing a continuous distribution while retaining its survival function. The statistical properties of the discrete Erlang-truncated exponential distribution such as the quantile function, moments, moment generating function, Rényi entropy and order statistics are calculated. The estimation of the parameters of the model is approached by the maximum likelihood (ML) method. The stress-strength parameter is obtained and estimated by using ML method.
