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Showing 6 results for Subject:
Ameneh Kheradmandi, Nahid Sanjari Fasipour,
Volume 3, Issue 1 (9-2009)
Abstract
Gomez et al. (2007) introduced the skew t-normal distribution, showing that it is a good alternative to model heavy tailed data with strong symmetrical nature, specially because it has a larger range of skewness than the skew-normal distribution. Gomez et al. (2007) and Lin et al. (2009) described some properties of this distribution. In this paper, we consider some further properties of skew student-t-normal distribution. Also, we present four theorems for constructing of this distribution. Next we illustrate a numerical example to model the Vanadium pollution data in the Shadegan Wetland by using skew student-t-normal distribution.
Nahid Sanjari Farsipour, Hajar Riyahi,
Volume 7, Issue 2 (3-2014)
Abstract
In this paper the likelihood and Bayesian inference of the stress-strength reliability are considered based on record values from proportional and proportional reversed hazard rate models. Then inference of the stress-strength reliability based on lower record values from some generalized distributions are also considered. Next the likelihood and Bayesian inference of the stress-strength model based on upper record values from Gompertz, Burr type XII, Lomax and Weibull distributions are considered. The ML estimators and their properties are studied. Likelihood-based confidence intervals, exact, as well as the Bayesian credible sets and bootstrap interval for the stress-strength reliability in all distributions are obtained. Simulation studies are conducted to investigate and compare the performance of the intervals.
Maryam Ahangari, Sedigheh Shams,
Volume 13, Issue 1 (9-2019)
Abstract
One of the applicable tools, in order to develop the economy's politics, is Iranian's cooperation in increasing their level of public knowledge and the humanization of economic. Economical index, rate, price, and percentage are not informative only. From this point of view, one of the scientific ways to study the economic data is "Statistical Modeling" through the applicable concept of "Copula Function". In this paper, through the copula functions and the applicable concept of dependence, called "Directional dependence", the dependence structure between variations in family's income and the expenses allocated to buy cultural and miscellaneous goods would be widely studied. Simulation results show that by decreasing the level of income, Iranian families tend to decrease their cultural costs rather than unnecessary miscellaneous costs.
Ronak Jamshidi, Sedigheh Shams,
Volume 13, Issue 2 (2-2020)
Abstract
In this paper, a family of copula functions called chi-square copula family is used for modeling the dependency structure of stationary and isotropic spatial random fields. The dependence structure of this copula is such that, it generalizes the Gaussian copula and flexible for modeling for high-dimensional random vectors and unlike Gaussian copula it allows for modeling of tail asymmetric dependence structures. Since the density function of chi-square copula in high dimension has computational complexity, therefore to estimate its parameters, a composite pairwise likelihood method is used in which only bivariate density functions are used. The purpose of this paper is to investigate the properties of the chi-square copula family, estimating its parameters with the composite pairwise likelihood and its application in spatial interpolation.
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.
Dr. Mahdi Alimohammadi, Mrs. Rezvan Gharebaghi,
Volume 19, Issue 2 (4-2025)
Abstract
It was proved about 60 years ago that if a continuous random variable X has an increasing failure rate then its order statistics will also be increasing failure rate, and this problem remained unproved for the discrete case until recently a proof method using an integral inequality was provided. In this article, we present a completely different method to solve this problem.
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