The parameter estimation and the coefficient of contamination for the regression models with repeated measures are studied when its response variables are contaminated by another random variable sequence.Under the sui...The parameter estimation and the coefficient of contamination for the regression models with repeated measures are studied when its response variables are contaminated by another random variable sequence.Under the suitable conditions it is proved that the estimators which are established in the paper are strongly consistent estimators.展开更多
Portfolio selection is an important issue in finance and it involves the balance between risk and return. This paper investigates portfolio selection under Mean-CVa R model in a nonparametric framework with α-mixing ...Portfolio selection is an important issue in finance and it involves the balance between risk and return. This paper investigates portfolio selection under Mean-CVa R model in a nonparametric framework with α-mixing data as financial data tends to be dependent. Many works have provided some insight into the performance of portfolio selection from the aspects of data and simulation while in this paper we concentrate on the asymptotic behaviors of the optimal solutions and risk estimation in theory.展开更多
In this paper, a new estimator of the shape parameter in the family of Gamma distribution is constructed by using the moment idea, and it is proved that this estimator is strongly consistent and asymptotically normal.
Let {X\-n,n≥1} be a stationary strongly mixing random sequence satisfying E X\-1=μ, E X\+2\-1<∞ and (Var S\-n)/n→σ\+2 as n→∞ . In this paper a class of estimators of Var S\-n is studied. Th...Let {X\-n,n≥1} be a stationary strongly mixing random sequence satisfying E X\-1=μ, E X\+2\-1<∞ and (Var S\-n)/n→σ\+2 as n→∞ . In this paper a class of estimators of Var S\-n is studied. The weak consistency and asymptotic normality as well as the central limit theorem are presented.展开更多
For the linear model y_i=x_iθ+e_i, i=1, 2,…, let the error sequence {e_i}_i=1 be iidr.v.’s, with unknown density f(x). In this paper,a nonparametric estimation method based onthe residuals is proposed for estimatin...For the linear model y_i=x_iθ+e_i, i=1, 2,…, let the error sequence {e_i}_i=1 be iidr.v.’s, with unknown density f(x). In this paper,a nonparametric estimation method based onthe residuals is proposed for estimating f(x) and the consistency of the estimators is obtained.展开更多
In this paper, we consider whether the random effect exists in linear mixed models （LMMs） when only moment conditions are assumed. Based on the estimators of parameters and their asymptotic properties, a Wald-type t...In this paper, we consider whether the random effect exists in linear mixed models （LMMs） when only moment conditions are assumed. Based on the estimators of parameters and their asymptotic properties, a Wald-type test is constructed. It is consistent against global alternatives and is sensitive to the local alternatives converging to the null hypothesis at parametric rates, a fastest possibly rate for goodness-of-fit testing. Moreover, a simulation study shows the performance of the test is good. The procedure also applies to a real data.展开更多
In this article, a class of Mantel-Haenszel type estimators of hazard ratios in proportional hazards model is presented for simple nested case-control study. The estimators have the form of the Mantel-Haenszel estimat...In this article, a class of Mantel-Haenszel type estimators of hazard ratios in proportional hazards model is presented for simple nested case-control study. The estimators have the form of the Mantel-Haenszel estimator of odds ratios, and it is shown that the estimators are dually cousistent, and asymptotically normal. Dually consistently estimated covariance matrices of the proposed estimators are also developed. An example is given to illustrate the estimators.展开更多
In this paper, a bias-eliminated subspace identification method is proposed for industrial applications subject to colored noise. Based on double orthogonal projections, an identification algorithm is developed to eli...In this paper, a bias-eliminated subspace identification method is proposed for industrial applications subject to colored noise. Based on double orthogonal projections, an identification algorithm is developed to eliminate the influence of colored noise for consistent estimation of the extended observability matrix of the plant state-space model. A shift-invariant approach is then given to retrieve the system matrices from the estimated extended observability matrix. The persistent excitation condition for consistent estimation of the extended observability matrix is analyzed. Moreover, a numerical algorithm is given to compute the estimation error of the estimated extended observability matrix. Two illustrative examples are given to demonstrate the effectiveness and merit of the proposed method.展开更多
文摘The parameter estimation and the coefficient of contamination for the regression models with repeated measures are studied when its response variables are contaminated by another random variable sequence.Under the suitable conditions it is proved that the estimators which are established in the paper are strongly consistent estimators.
基金Supported by the Fundamental Research Funds for the Central UniversitiesMajor Project of the National Social Science Foundation of China(13&ZD163)Zhejiang Provincial Natural Science Foundation(LY13A010001 and LY17A010016)
文摘Portfolio selection is an important issue in finance and it involves the balance between risk and return. This paper investigates portfolio selection under Mean-CVa R model in a nonparametric framework with α-mixing data as financial data tends to be dependent. Many works have provided some insight into the performance of portfolio selection from the aspects of data and simulation while in this paper we concentrate on the asymptotic behaviors of the optimal solutions and risk estimation in theory.
文摘In this paper, a new estimator of the shape parameter in the family of Gamma distribution is constructed by using the moment idea, and it is proved that this estimator is strongly consistent and asymptotically normal.
文摘Let {X\-n,n≥1} be a stationary strongly mixing random sequence satisfying E X\-1=μ, E X\+2\-1<∞ and (Var S\-n)/n→σ\+2 as n→∞ . In this paper a class of estimators of Var S\-n is studied. The weak consistency and asymptotic normality as well as the central limit theorem are presented.
基金The project supported by National Natural Science Foundation of China Crant 18971061
文摘For the linear model y_i=x_iθ+e_i, i=1, 2,…, let the error sequence {e_i}_i=1 be iidr.v.’s, with unknown density f(x). In this paper,a nonparametric estimation method based onthe residuals is proposed for estimating f(x) and the consistency of the estimators is obtained.
基金Supported by a grant (HKBU2030/07P) from the Research Grants Council of Hong Kongthe National Natural Science Foundation of China (Grant No. 10871001)+2 种基金the Humanities and Social Sciences Project of Chinese Ministry of Education (Grant No. 08JC910002)Zhejiang Provincial Natural Science Foundation of China (Grant No. Y6090172)Youth Talent Foundation of Zhejiang Gongshang University, China
文摘In this paper, we consider whether the random effect exists in linear mixed models （LMMs） when only moment conditions are assumed. Based on the estimators of parameters and their asymptotic properties, a Wald-type test is constructed. It is consistent against global alternatives and is sensitive to the local alternatives converging to the null hypothesis at parametric rates, a fastest possibly rate for goodness-of-fit testing. Moreover, a simulation study shows the performance of the test is good. The procedure also applies to a real data.
基金Education Ministry Fund For Returned Students and Beijing Natural ScienceFoundation.
文摘In this article, a class of Mantel-Haenszel type estimators of hazard ratios in proportional hazards model is presented for simple nested case-control study. The estimators have the form of the Mantel-Haenszel estimator of odds ratios, and it is shown that the estimators are dually cousistent, and asymptotically normal. Dually consistently estimated covariance matrices of the proposed estimators are also developed. An example is given to illustrate the estimators.
基金This work was supported by the National Thousand Talents Program of China, the National Natural Science Foundation of China （Nos. 61473054, 61633006）, and the Fundamental Research Funds for the Central Universities of China （No. DUT15ZD108）.
文摘In this paper, a bias-eliminated subspace identification method is proposed for industrial applications subject to colored noise. Based on double orthogonal projections, an identification algorithm is developed to eliminate the influence of colored noise for consistent estimation of the extended observability matrix of the plant state-space model. A shift-invariant approach is then given to retrieve the system matrices from the estimated extended observability matrix. The persistent excitation condition for consistent estimation of the extended observability matrix is analyzed. Moreover, a numerical algorithm is given to compute the estimation error of the estimated extended observability matrix. Two illustrative examples are given to demonstrate the effectiveness and merit of the proposed method.
