A definition of generalized admissibility of Bayes estimates has been given. This generalized admissibility is a rule to identify whether Bayes estimates is acceptable or not under the condition of incorrect prior inf...A definition of generalized admissibility of Bayes estimates has been given. This generalized admissibility is a rule to identify whether Bayes estimates is acceptable or not under the condition of incorrect prior information. In this paper, a sufficient and necessary condition for the generalized admissibility is derived under quadratic loss. From this we can conclude that, when deviation of prior mean and deviation of prior variance do not go beyond the bound, the Bayes estimation is acceptable and it is discussed that how the deviation of the prior information influences on generalized admissibility. Because the precise distribution of prior information is unknown, the example gives a way to select the prior distribution. The example shows that this method is efficient and feasible.展开更多
For multivariate linear model Y=XΘ+ε, ~N(0, σ 2ΣV), this paper is concerned with the admissibility of linear estimators of estimable function SXΘ in the class of all estimators. All admissible linear estimators ...For multivariate linear model Y=XΘ+ε, ~N(0, σ 2ΣV), this paper is concerned with the admissibility of linear estimators of estimable function SXΘ in the class of all estimators. All admissible linear estimators of SXΘ are given under each of four definitions of admissibility.展开更多
This article mainly discusses the admissibility of quadratic estimate of covariance in pseudoelliptical distribution. Under the quadratic loss function, the necessary and sufficient conditions that a quadratic estimat...This article mainly discusses the admissibility of quadratic estimate of covariance in pseudoelliptical distribution. Under the quadratic loss function, the necessary and sufficient conditions that a quadratic estimator is an admissible estimator of covariance in the class of quadratic estimators are obtained. A complete class of the quadratic estimator class is also given.展开更多
This paper is concerned with tile proOlenl or improving hue ~lma^u~ u~ under Stein＇s loss. By the partial Iwasawa coordinates of covariance matrix, the corresponding risk can be split into three parts. One can use th...This paper is concerned with tile proOlenl or improving hue ~lma^u~ u~ under Stein＇s loss. By the partial Iwasawa coordinates of covariance matrix, the corresponding risk can be split into three parts. One can use the information in the weighted matrix of weighted quadratic loss to improve one part of risk. However, this paper indirectly takes advantage of the information in the sample mean and reuses Iwasawa coordinates to improve the rest of risk. It is worth mentioning that the process above can be repeated. Finally, a Monte Carlo simulation study is carried out to verify the theoretical results.展开更多
For the general fixed effects linear model: Y = X_T+ε, ε～N(0, V), V≥0, weobtain the necessary and sufficient conditions for LY +a to be admissible for a linear estimablefunction S_r in the class of all estimators ...For the general fixed effects linear model: Y = X_T+ε, ε～N(0, V), V≥0, weobtain the necessary and sufficient conditions for LY +a to be admissible for a linear estimablefunction S_r in the class of all estimators under the loss function (d -- Sr)'D(d --Sr), whereD≥0 is known. For the general random effects linear model: Y = Xβ+ε,(βε)～N((Aα 0), (V_(11)V_(12)V_(21)V_(22))), ∧= XV_(11)X'+XV_(12)+ V_(21)X+V_(22)≥0, we also get the necessaryand sufficient conditions for LY+a to be admissible for a linear estimable function Sα+Qβin the class of all estimators under the loss function (d-Sα-Qβ)'D(d-Sα-Qβ).whereD≥0 is known.展开更多
基金Project supported by the Excellent Young Teachers Programof MOE of china
文摘A definition of generalized admissibility of Bayes estimates has been given. This generalized admissibility is a rule to identify whether Bayes estimates is acceptable or not under the condition of incorrect prior information. In this paper, a sufficient and necessary condition for the generalized admissibility is derived under quadratic loss. From this we can conclude that, when deviation of prior mean and deviation of prior variance do not go beyond the bound, the Bayes estimation is acceptable and it is discussed that how the deviation of the prior information influences on generalized admissibility. Because the precise distribution of prior information is unknown, the example gives a way to select the prior distribution. The example shows that this method is efficient and feasible.
文摘For multivariate linear model Y=XΘ+ε, ~N(0, σ 2ΣV), this paper is concerned with the admissibility of linear estimators of estimable function SXΘ in the class of all estimators. All admissible linear estimators of SXΘ are given under each of four definitions of admissibility.
基金The research was partially supported by the Doctoral Programme of Higher Education(No.20020027010)of China.
文摘This article mainly discusses the admissibility of quadratic estimate of covariance in pseudoelliptical distribution. Under the quadratic loss function, the necessary and sufficient conditions that a quadratic estimator is an admissible estimator of covariance in the class of quadratic estimators are obtained. A complete class of the quadratic estimator class is also given.
基金supported by the National Natural Science Foundation of China under Grant No.11371236the Graduate Student Innovation Foundation of Shanghai University of Finance and Economics(CXJJ-2015-440)
文摘This paper is concerned with tile proOlenl or improving hue ~lma^u~ u~ under Stein＇s loss. By the partial Iwasawa coordinates of covariance matrix, the corresponding risk can be split into three parts. One can use the information in the weighted matrix of weighted quadratic loss to improve one part of risk. However, this paper indirectly takes advantage of the information in the sample mean and reuses Iwasawa coordinates to improve the rest of risk. It is worth mentioning that the process above can be repeated. Finally, a Monte Carlo simulation study is carried out to verify the theoretical results.
文摘For the general fixed effects linear model: Y = X_T+ε, ε～N(0, V), V≥0, weobtain the necessary and sufficient conditions for LY +a to be admissible for a linear estimablefunction S_r in the class of all estimators under the loss function (d -- Sr)'D(d --Sr), whereD≥0 is known. For the general random effects linear model: Y = Xβ+ε,(βε)～N((Aα 0), (V_(11)V_(12)V_(21)V_(22))), ∧= XV_(11)X'+XV_(12)+ V_(21)X+V_(22)≥0, we also get the necessaryand sufficient conditions for LY+a to be admissible for a linear estimable function Sα+Qβin the class of all estimators under the loss function (d-Sα-Qβ)'D(d-Sα-Qβ).whereD≥0 is known.
