经验似然中无偏估计函数的选择问题

由Owen(1988)提出的经验似然是一种重要的统计方法．本文主要研究经验似然的基础之一——无偏估计函数的选择问题。为此，定义了基于最优无偏估计函数的最优经验似然，得到了最优无偏估计函数的性质，研究了最优无偏估计函数的构造方法．最后，将这种方法推广到拟似然。     

权回归模型下几种估计性能的比较

在给定的权回归模型下,讨论了最小二乘估计、最优加权最小二乘估计和线性无偏最小方差估计的性能比较,得出了在随机误差方差矩阵可逆条件下,可算出最优加权最小二乘估计与线性无偏最小方差估计误差方差阵的差表达式,并在一定条件下,两者趋于一致。     

用修正系数法构造θ~2的无偏估计

在总体分布为指数分布和均匀分布时,由未知参数θ的无偏估计量,通过修正系数法直接构造θ2的无偏估计量.     

LSE相对于一般广义岭估计的效率下界

考察一般Gauss-Markov模型中未知参数向量β的估计的改造问题,进一步讨论了方兴等人提出的一种估计的相对效率,对其部分结果进行推广,得到LSE相对于一般广义岭估计的效率的下界.     

模糊随机向量的性质及在回归模型中的应用

该文研究了模糊随机向量的性质，并将其应用于带有随机干扰的模糊线性回归模型，得到了它的渐进无偏模型，给出了它的近似最优估计。     

MIXED LINEAR MODEL APPROACHES FOR ANALYZING GENETIC MODELS OF COMPLEX QUANTITATIVE TRAITS

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一般广义岭估计的效率上界

考察一般Gauss-Markov模型中未知参数向量的最优线性无偏估计的改造问题,讨论了方兴等人提出的最优化无偏估计的一种估计的相对效率,把该文中给出的一般岭估计的相对效率的上界,推广到一般广义岭估计的相对效率的上界.yh     

Mixed linear model approaches for analyzing genetic models of complex quantitative traits

New approaches based on general mixed linear models were presented for analyzing complex quantitative traits in animal models, seed models and QTL (quantitative trait locus) mapping models. Variances and covariances can be appropriately estimated by MINQUE (minimum norm quadratic unbiased estimation) approaches. Random genetic effects can be predicted without bias by LUP (linear unbiased prediction) or AUP (adjusted unbiased prediction) methods. Mixed-model based composite interval mapping (MCIM) methods are suitable for efficiently searching QTLs along the whole genome. Bayesian methods and Markov Chain Monte Carlo (MCMC) methods can be applied in analyzing parameters of random effects as well as their variances. Projects supported by NSFC (39670390, 39893350) and the NIH Grant GM32518     

一致最小方差无偏估计判定准则的新证法

文中通过构造Hilbert空间,应用Hilbert空间性质给出一种证明一致最小方差无偏估计判定准则的新方法,并给出该判定准则在Hilbert空间的几何直观意义.     

Terminology and methods in the education of the deaf. Questions for the experts.

As an outsider interested in the methodologies currently used to educate deaf children, I have many questions about the ambiguous terminology, continuing controversies, and lack of unbiased, scientific research. The questions concern issues such as the difference between Deaf and deaf, the feasibility of the ASL/ESL proposal, and the disappointing lack of definitive answers and unbiased evidence favoring any one particular method.     

方差分量模型参数估计问题研究

方差分量模型的随机效应的协方差为单位阵时<线性模型引论>已进行研究.把随机效应的协方差推广为正定阵进行研究.用最小范数二次无偏估计法给出方差分量的估计.     

Definition and Measurement of Selection Bias: From Constant Ratio to Constant Difference

Despite its intuitive appeal and popularity, Thorndike's constant ratio (CR) model for unbiased selection is inherently inconsistent in n -free selection. Satisfaction of the condition for unbiased selection, when formulated in terms of success/acceptance probabilities, usually precludes satisfaction by the converse probabilities of rejection/failure, and vice versa. This paper suggests that this inconsistency is unavoidable due to the (negative) linear relation between "percent accepted" ( P ) and "percent rejected" (1 – P ), which does not preserve ratios and, thus, invalidates the conceptualization and measurement of selection bias in ratio terms. Therefore, we propose to substitute the CR model with a constant difference (CD) model for the definition and measurement of selection bias, and show the latter's underlying rationale and its applicability in both n -free and fixed- n selection.     

The Role of Centering for Interaction of Level 1 Variables in Multilevel Structural Equation Models

This article examined the role of centering in estimating interaction effects in multilevel structural equation models. Interactions are typically represented by product term of 2 variables that are hypothesized to interact. In multilevel structural equation modeling (MSEM), the product term involving Level 1 variables is decomposed into within-cluster and between-cluster random components. The choice of centering affects the decomposition of the product term, and therefore affects the sample variance and covariance associated with the product term used in the maximum likelihood fitting function. The simulation study showed that for an interaction between a Level 1 variable and a Level 2 variable, the product term of uncentered variables or the product term of grand mean centered variables produced unbiased estimates in both Level 1 and Level 2 models. The product term of cluster mean centered variables produced biased estimates in the Level 1 model. For an interaction between 2 Level 1 variables, the product term of cluster mean centered variables produced unbiased estimates in the Level 1 model, whereas the product term of grand mean centered variables produced unbiased estimates for the Level 1 model. Recommendations for researchers who wish to estimate interactions in MSEM are provided.     

均匀分布中参数θ的估计量的比较

结合教学中遇到的问题,举例分析和说明了仅有无偏性不足以判定一个估计的好坏。     

Correlations in dice throwing experiment

We consider three waiting type experiments involving throws of an unbiased die and study the correlation coefficients among the involved random variables.     

对数正态分布参数的最大似然估计

利用最大似然估计法求出了对数正态分布两个参数的估计量，并讨论了它们的无偏性和相合性。     

非线性回归模型中的拟Fisher信息

给出拟Fisher信息达到其上界的充要条件,此条件为真得分函数是线性无偏的,即观测数据来自指数族分布,当拟Fisher信息太小时,提出了一种线性有偏拟得分方法,该方法能增加拟Fisher信息,从而改进了参数估计。     

关于“一致估计”几个定理的推广

对概率统计中的点估计的一致性问题进行了讨论，内容涉及参数的无偏估计、一致估计、均方一致估计等。     

WVD和XWVD的统计特征分析

1　Introduction　TheWigner Villedistribution (WVD) [1 7] hasbeenshowntobeefficientintheestimationofinstanta neousfrequency (IF)ofasignal.BecauseWVDisofbettertime frequencyresolutionandabletolocateen ergybasedontheIFlaw ,especiallyforalinearfre quencymodulated(LFM )signalwithaconstantampli tude,WVDwillreducetoarowofdeltafunctions .ThereforeonecanobtainanunbiasedestimateofIFofthesignalusingthepeakofWVD .Butperformanceofthepeakestimatorisdegradedsignificantlywithesti mationvariance quic…     

R-S（t）半随机过程模型结构可靠度的最小方差无偏估计

讨论强度为指数分布,应力为强度函数毫（l）∑（i=0）λit^i的复合非时齐Poisson过程模型结构可靠度的估计问题．获得强度函数（l）∑（i=0）λit^i的复合非时齐Poisson过程的最大值分布与当量正态变量,指数分布一强度函数（l）∑（i=0）λit^i的复合非时齐Poisson过程模型结构可靠度的最小方差无偏估计．