This paper studies the identification of linear systems with quantized output observations.Recursive estimates for the linear system and the quantization thresholds are derived by the stochastic approximation algorith...This paper studies the identification of linear systems with quantized output observations.Recursive estimates for the linear system and the quantization thresholds are derived by the stochastic approximation algorithms with expanding truncations(SAAWET).Under suitable conditions,it is shown that the estimates converge to the true values almost surely.展开更多
In this paper we study p-variation of bifractional Brownian motion. As an applica-tion, we introduce a class of estimators of the parameters of a bifractional Brownian motion andprove that both of them are strongly co...In this paper we study p-variation of bifractional Brownian motion. As an applica-tion, we introduce a class of estimators of the parameters of a bifractional Brownian motion andprove that both of them are strongly consistent; as another application, we investigate fractalnature related to the box dimension of the graph of bifractional Brownian motion.展开更多
In this paper, we consider the power variation of subfractional Brownian mo- tion. As an application, we introduce a class of estimators for the index of a subfractional Brownian motion and show that they are strongly...In this paper, we consider the power variation of subfractional Brownian mo- tion. As an application, we introduce a class of estimators for the index of a subfractional Brownian motion and show that they are strongly consistent.展开更多
This article concerded with a semiparametric generalized partial linear model （GPLM） with the type Ⅱ censored data. A sieve maximum likelihood estimator （MLE） is proposed to estimate the parameter component, allo...This article concerded with a semiparametric generalized partial linear model （GPLM） with the type Ⅱ censored data. A sieve maximum likelihood estimator （MLE） is proposed to estimate the parameter component, allowing exploration of the nonlinear relationship between a certain covariate and the response function. Asymptotic properties of the proposed sieve MLEs are discussed. Under some mild conditions, the estimators are shown to be strongly consistent. Moreover, the estimators of the unknown parameters are asymptotically normal and efficient, and the estimator of the nonparametric function has an optimal convergence rate.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.11571186
文摘This paper studies the identification of linear systems with quantized output observations.Recursive estimates for the linear system and the quantization thresholds are derived by the stochastic approximation algorithms with expanding truncations(SAAWET).Under suitable conditions,it is shown that the estimates converge to the true values almost surely.
基金supported by NSFC (11071076)NSFC-NSF (10911120392)
文摘In this paper we study p-variation of bifractional Brownian motion. As an applica-tion, we introduce a class of estimators of the parameters of a bifractional Brownian motion andprove that both of them are strongly consistent; as another application, we investigate fractalnature related to the box dimension of the graph of bifractional Brownian motion.
基金supported by National Natural Science Foundation of China(11271020)Natural Science Foundation of Anhui Province(1208085MA11,1308085QA14)+3 种基金Key Natural Science Foundation of Anhui Educational Committee(KJ2011A139,KJ2012ZD01,KJ2013A133)supported by National Natural Science Foundation of China(11171062)Innovation Program of Shanghai Municipal Education Commission(12ZZ063)supported by Mathematical Tianyuan Foundation of China(11226198)
文摘In this paper, we consider the power variation of subfractional Brownian mo- tion. As an application, we introduce a class of estimators for the index of a subfractional Brownian motion and show that they are strongly consistent.
基金The talent research fund launched (3004-893325) of Dalian University of Technologythe NNSF (10271049) of China.
文摘This article concerded with a semiparametric generalized partial linear model （GPLM） with the type Ⅱ censored data. A sieve maximum likelihood estimator （MLE） is proposed to estimate the parameter component, allowing exploration of the nonlinear relationship between a certain covariate and the response function. Asymptotic properties of the proposed sieve MLEs are discussed. Under some mild conditions, the estimators are shown to be strongly consistent. Moreover, the estimators of the unknown parameters are asymptotically normal and efficient, and the estimator of the nonparametric function has an optimal convergence rate.
