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Showing 5 results for Survival Function
Aref Khanjari Idenak, Mohammadreza Zadkarami, Alireza Daneshkhah,
Volume 5, Issue 2 (2-2012)
Abstract
In this paper a new compounding distribution with increasing, decreasing, bathtub shaped and unimodal-bathtub shaped hazard rate function. The new three-parameters distribution as a generalization of the exponential power distribution is proposed. Maximum likelihood estimation of the parameters, raw-moments, density function of the order statistics, survival function, hazard rate function, mean residual lifetime, reliability function and median are presented. Then the properties of this distribution are illustrated based on a real data set.
Aref Khanjari Idenak, Mohammadreza Zadkarami, Alireza Daneshkhah,
Volume 8, Issue 2 (3-2015)
Abstract
In this paper a new compounding distribution with increasing, decreasing, bathtub shaped and unimodal hazard rate function is proposed. The new four-parameters distribution is a generalization of the complementary exponential power distribution. The raw-moments, density function of the order statistics, survival function, hazard rate function, quantiles, mean residual lifetime and reliability function are presented. The estimation of the new distribution in a special case Poisson complementary exponential power distribution is studied by the method of maximum likelihood and EM algorithm. Expression for asymptotic distribution for the maximum likelihood estimation of the parameters of the PCEP distribution are obtained and for determining the precision of the variance and covariance of the estimations, a simulation is used, Then experimental results are illustrated based on the real data set.
Eisa Mahmoudi, Somayeh Abolhosseini,
Volume 10, Issue 1 (8-2016)
Abstract
In this paper we propose a new two-parameters distribution, which is an extension of the Lindley distribution with increasing and bathtub-shaped failure rate, called as the Lindley-logarithmic (LL) distribution. The new distribution is obtained by compounding Lindley (L) and Logarithmic distributions. We obtain several properties of the new distribution such as its probability density function, its failure rate functions, quantiles and moments. The maximum likelihood estimation procedure via a EM-algorithm is presented in this paper. At the end, in order to show the flexibility and potentiality of this new class, some series of real data is used to fit.
Bahram Tarami, Mohsen Avaji, Nahid Sanjari Farsipour,
Volume 15, Issue 1 (9-2021)
Abstract
In this paper, using the extended Weibull Marshall-Olkin-Nadarajah family of distributions, the exponential, modified Weibull, and Gompertz distributions are obtained, and density, survival, and hazard functions are simulated. Next, an algorithm is presented for the simulation of these distributions. For exponential case, Bayesian statistics under squared error, entropy Linex, squared error loss functions and modified Linex are calculated. Finally, the presented distributions are fitted to a real data set.
Mahdieh Mozafari, Mohammad Khanjari Sadegh, , Gholamreza Hesamian,
Volume 17, Issue 1 (9-2023)
Abstract
In this paper, some reliability concepts have been investigated based on the α-pessimistic and its relationship with the α-cut of a fuzzy number. For this purpose, if the lifetime distribution of the system components is known, using the definition of the scale fuzzy random variable, based on α-pessimistic, some reliability criteria have been investigated. Also, suppose the lifetime distribution of the components is unknown or only the fuzzy observations of the lifetime of the features are available. In that case, the empirical distribution function of the fuzzy data is used to estimate the reliability, and some examples are provided to illustrate the results.
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