This paper considers the problem of change point in single index models.In order to obtain asymptotically valid confidence intervals for the estimation of the change point,the convergence rate and asymptotic distribut...This paper considers the problem of change point in single index models.In order to obtain asymptotically valid confidence intervals for the estimation of the change point,the convergence rate and asymptotic distribution of the change point estimate is studied.Some simulation results are presented which show that the numerical performance of our estimator is satisfactory.展开更多
In this paper, the authors consider an adaptive recursive algorithm by selecting an adaptive sequence for computing M-estimators in multivariate linear regression models. Its asymptotic property is investigated. The r...In this paper, the authors consider an adaptive recursive algorithm by selecting an adaptive sequence for computing M-estimators in multivariate linear regression models. Its asymptotic property is investigated. The recursive algorithm given by Miao and Wu （1996） is modified accordingly. Simu- lation studies of the Mgorithm is also provided. In addition, the Newton-Raphson iterative algorithm is considered for the purpose of comparison.展开更多
Assume that the characteristic index α of stable distribution satisfies 1 < α < 2, and that the distribution is symmetrical about its mean. We consider the change point estimators for stable distribution with ...Assume that the characteristic index α of stable distribution satisfies 1 < α < 2, and that the distribution is symmetrical about its mean. We consider the change point estimators for stable distribution with α or scale parameter β shift. For the one case that mean is a known constant, if α or β changes, then density function will change too. To this end, we suppose the kernel estimation for a change point. For the other case that mean is an unknown constant, we suppose to apply empirical characteristic function to estimate the change-point location. In the two cases, we consider the consistency and strong convergence rate of estimators. Furthermore, we consider the mean shift case. If mean changes, then corresponding characteristic function will change too. To this end, we also apply empirical characteristic function to estimate change point. We obtain the similar convergence rate. Finally, we consider its application on the detection of mean shift in financial market.展开更多
基金supported by National Natural Science Foundation for Young Scientists of China(Grant Nos.11101397,11201108)the Humanities and Social Sciences Project from Ministry of Education of China(Grant No.12YJC910007)+1 种基金Anhui Provincial Natural Science Foundation(Grant No.1208085QA12)the National Statistical Research Plan Project(Grant No.2012LZ009)
文摘This paper considers the problem of change point in single index models.In order to obtain asymptotically valid confidence intervals for the estimation of the change point,the convergence rate and asymptotic distribution of the change point estimate is studied.Some simulation results are presented which show that the numerical performance of our estimator is satisfactory.
基金supported by the National Natural Science Foundation for Young Scientists of China under Grant No.11101397the Natural Sciences and Engineering Research Council of Canada
文摘In this paper, the authors consider an adaptive recursive algorithm by selecting an adaptive sequence for computing M-estimators in multivariate linear regression models. Its asymptotic property is investigated. The recursive algorithm given by Miao and Wu （1996） is modified accordingly. Simu- lation studies of the Mgorithm is also provided. In addition, the Newton-Raphson iterative algorithm is considered for the purpose of comparison.
基金the National Natural Science Foundation of China (Grant No.10471135) Graduate Innovation Fund of the University of Science and Technology of China (Grant No.KD2006063)
文摘Assume that the characteristic index α of stable distribution satisfies 1 < α < 2, and that the distribution is symmetrical about its mean. We consider the change point estimators for stable distribution with α or scale parameter β shift. For the one case that mean is a known constant, if α or β changes, then density function will change too. To this end, we suppose the kernel estimation for a change point. For the other case that mean is an unknown constant, we suppose to apply empirical characteristic function to estimate the change-point location. In the two cases, we consider the consistency and strong convergence rate of estimators. Furthermore, we consider the mean shift case. If mean changes, then corresponding characteristic function will change too. To this end, we also apply empirical characteristic function to estimate change point. We obtain the similar convergence rate. Finally, we consider its application on the detection of mean shift in financial market.
