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Showing 7 results for Copula Function
Abouzar Bazyari,
Volume 6, Issue 1 (8-2012)
Abstract
In the individual risk processes of an insurance company with dependent claim sizes, determination of the ruin probability and time to ruin are very important. Exact computing of theses probabilities, because of it's complex structure, is not easy. In this paper, Monte Carlo simulation method is used to obtain the ruin probabilities estimates, times to ruin and confidence interval for the ruin probability estimates of the mentioned process for different dependence level of claims. In this simulation the multivariate Frank copula function and Marshall and Olkin's algorithm are provided to generate the dependent claims. Then it has shown that with increasing the dependence level of claim sizes the ruin probability of the risk process increases, while its time to ruin decreases
Mohammad Amini, Hadi Jabbari Noughabi, Mahla Ghasemnejad Farsangi,
Volume 6, Issue 2 (2-2013)
Abstract
In this paper, three new non-parametric estimator for upper tail dependence measure are introduced and it is shown that these estimators are consistent and asymptotically unbiased. Also these estimators are compared using the Mont Carlo simulation of three different copulas and present a new method in order to select the best estimator by applying the real data.
Mina Godazi, Mohammadreza Akhoond, Abdolrahman Rasekh Rasekh,
Volume 10, Issue 1 (8-2016)
Abstract
One of the methods that in recent years has attracted the attention of many researchers for modeling multivariate mixed outcome data is using the copula function. In this paper a regression model for mixed survival and discrete outcome data based on copula function is proposed. Where the continuous variable was time and could has censored observations. For this task it is assumed that marginal distributions are known and a latent variable was used to transform discrete variable to continuous. Then by using a copula function, the joint distribution of two variables was constructed and finally the obtained model was used to model birth interval data in Ahwaz city in south-west of Iran.
Shahrokh Hashemi-Bosra, Ebrahim Salehi,
Volume 11, Issue 1 (9-2017)
Abstract
The (n-k+1)-out-of-n systems are important types of coherent systems and have many applications in various areas of engineering. In this paper, the general inactivity time of failed components of (n-k+1)-out-of-n system is studied when the system fails at time t>0. First we consider a parallel system including two exchangeable components and then using Farlie-Gumbel-Morgenstern copula, investigate the behavior of mean inactivity time of failed components of the system. In the next part, (n-k+1)-out-of-n systems with exchangeable components are considered and then, some stochastic ordering properties of the general inactivity time of the systems are presented based on one sample or two samples.
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.
Ghobad Barmalzan,
Volume 13, Issue 1 (9-2019)
Abstract
In this paper, under certain conditions, the usual stochastic, convex and dispersive orders between the smallest claim amounts with independent Weibull claims are discussed. Also, under conditions on some well-known common copula, some stochastic comparisons of smallest claim amounts with dependent heterogeneous claims have been obtained.
Dr. Abouzar Bazyari,
Volume 16, Issue 2 (3-2023)
Abstract
In this paper, the individual risk model of the insurance company with dependent claims is considered and assumes that the binary vector of random variables of claim sizes is independent. Also, they have a common joint distribution function. A recursive formula for infinite time ruin probability is obtained according to the initial reserve and joint probability density function of random variables of claim sizes using probability inequalities and the induction method. Some numerical examples and simulation studies are presented for checking the results related to the light-tailed bivariate Poisson, heavy-tailed Log-Normal and Pareto distributions. The results are compared for Farlie–Gambel–Morgenstern and bivariate Frank copula functions. The effect of claims with heavy-tailed distributions on the ruin probability is also investigated.
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