High frequency financial data is characterized by non-normality: asymmetric, leptokurtic and fat-tailed behaviour. The normal distribution is therefore inadequate in capturing these characteristics. To this end, vario...High frequency financial data is characterized by non-normality: asymmetric, leptokurtic and fat-tailed behaviour. The normal distribution is therefore inadequate in capturing these characteristics. To this end, various flexible distributions have been proposed. It is well known that mixture distributions produce flexible models with good statistical and probabilistic properties. In this work, a finite mixture of two special cases of Generalized Inverse Gaussian distribution has been constructed. Using this finite mixture as a mixing distribution to the Normal Variance Mean Mixture we get a Normal Weighted Inverse Gaussian (NWIG) distribution. The second objective, therefore, is to construct and obtain properties of the NWIG distribution. The maximum likelihood parameter estimates of the proposed model are estimated via EM algorithm and three data sets are used for application. The result shows that the proposed model is flexible and fits the data well.展开更多
In this paper,a new distribution called the extended inverse Gaussian(EIG)distribution is introduced.By means of the method of T-X family,the new distribution is compounded by the inverse Gaussian(IG)and Weibull distr...In this paper,a new distribution called the extended inverse Gaussian(EIG)distribution is introduced.By means of the method of T-X family,the new distribution is compounded by the inverse Gaussian(IG)and Weibull distributions.We study its fundamental properties,such as probability density function,hazard rate function,raw moments,moments generating function,skewness and kurtosis,and residual life.We also discuss the maximum likelihood estimators and asymptotic confident intervals of parameters in new distribution.Finally,the EIG distribution and several other competing distributions are fitted into an actual data set and it is shown that the EIG distribution has a superior performance among the compared distributions by making use of various goodness-of-fit tests.展开更多
In this paper, we propose a new generalized p-value for testing homogeneity of scale parameters λi from k independent inverse Gaussian populations. The proposed generalized p-value is proved to have exact frequentist...In this paper, we propose a new generalized p-value for testing homogeneity of scale parameters λi from k independent inverse Gaussian populations. The proposed generalized p-value is proved to have exact frequentist property, and it is also invariant under the group of scale transformation. Simulation results indicate that the proposed test is better than existing approximate χ^2 test.展开更多
文摘High frequency financial data is characterized by non-normality: asymmetric, leptokurtic and fat-tailed behaviour. The normal distribution is therefore inadequate in capturing these characteristics. To this end, various flexible distributions have been proposed. It is well known that mixture distributions produce flexible models with good statistical and probabilistic properties. In this work, a finite mixture of two special cases of Generalized Inverse Gaussian distribution has been constructed. Using this finite mixture as a mixing distribution to the Normal Variance Mean Mixture we get a Normal Weighted Inverse Gaussian (NWIG) distribution. The second objective, therefore, is to construct and obtain properties of the NWIG distribution. The maximum likelihood parameter estimates of the proposed model are estimated via EM algorithm and three data sets are used for application. The result shows that the proposed model is flexible and fits the data well.
基金Supported by the National Natural Science Foundation of China(12171335,12301603)the Science Development Project of Sichuan University(2020SCUNL201)the Scientific Foundation of Nanjing University of Posts and Telecommunications(NY221026)。
基金the National Natural Science Foundation of China(No.11861049)the Natural Science Foundation of Inner Mongolia(No.2017MS0101)。
文摘In this paper,a new distribution called the extended inverse Gaussian(EIG)distribution is introduced.By means of the method of T-X family,the new distribution is compounded by the inverse Gaussian(IG)and Weibull distributions.We study its fundamental properties,such as probability density function,hazard rate function,raw moments,moments generating function,skewness and kurtosis,and residual life.We also discuss the maximum likelihood estimators and asymptotic confident intervals of parameters in new distribution.Finally,the EIG distribution and several other competing distributions are fitted into an actual data set and it is shown that the EIG distribution has a superior performance among the compared distributions by making use of various goodness-of-fit tests.
基金Supported by the National Natural Science Foundation of China(Grant No.11201478,11471030,11126197 and11471035)
文摘In this paper, we propose a new generalized p-value for testing homogeneity of scale parameters λi from k independent inverse Gaussian populations. The proposed generalized p-value is proved to have exact frequentist property, and it is also invariant under the group of scale transformation. Simulation results indicate that the proposed test is better than existing approximate χ^2 test.
