"象同意异"与"象异意同"--试论先秦诗文比兴手法运用的一大特色

取象完全一致,但喻意不尽相同甚至截然不同的"象同意异"现象与取象全然不同,喻意却大致相仿甚至完全一样的"象异意同"现象在先秦诗文中大量存在,成为先秦诗文比兴手法运用的一大特色,文中主要研究探讨形成这一现象的诸多原因、所取得的独特效果以及对后世的深远影响.     

Fixed‐Effects Dynamic Panel Models,a Factor Analytical Method

We consider the estimation of dynamic panel data models in the presence of incidental parameters in both dimensions: individual fixed‐effects and time fixed‐effects, as well as incidental parameters in the variances. We adopt the factor analytical approach by estimating the sample variance of individual effects rather than the effects themselves. In the presence of cross‐sectional heteroskedasticity, the factor method estimates the average of the cross‐sectional variances instead of the individual variances. The method thereby eliminates the incidental‐parameter problem in the means and in the variances over the cross‐sectional dimension. We further show that estimating the time effects and heteroskedasticities in the time dimension does not lead to the incidental‐parameter bias even when T and N are comparable. Moreover, efficient and robust estimation is obtained by jointly estimating heteroskedasticities.     

两汉经略岭南述考

在岭南地方发展史上,两汉是一个十分重要的时期。两汉中央政权所采取的一系列经略岭南的重要措施,对于当时大一统帝国南疆的开拓和巩固,无疑起到了积极的作用,加强了对岭南地区的控制并促进了这一地区经济和文化的发展。     

论北宋法律制度中"例"的发展

中华法系是一种把成文法与判例法有机结合的法制,二者相得益彰.当代学者对宋代判例法的性质和意义往往认识不足,宋代的法制中已经产生了成文的<断例>.北宋的历史情况清楚地说明了判例法在中国的传统渊源.宋代"例"的发展可以看作是中国古代判例法及其实践步入成熟的关键时期,具有立法上的成文化和实践上的自觉因循之特点.     

论元杂剧的复仇精神

中国古代,允许无辜被害者的家属向加害者寻仇的法律制度,从春秋时期一直延续到元代,仍然被写进法律文本。它是元杂剧复仇精神的源头。元杂剧体现了传统文化背景下顽强的复仇理念。在复仇遇到阻碍时,为了达到复仇的目的往往借助清官侠客乃至鬼神     

Objective Bayesian Analysis of an Exponential Regression Model with Constrained Parameters Applied to Animal Digestibility

In animal digestibility the proportion of degraded food along the time has usually been modeled as a normal random variable with mean a function of the time and the following three parameters: the proportion of degraded food almost instantaneously, remaining proportion of food to be degraded, and velocity of degradation. The estimation of these parameters has been carried out mainly from a frequentist viewpoint by using the asymptotic distribution of the maximum likelihood estimator. This may give inadmissible estimates, such as values outside of the range of the parameters. This drawback could not appear if a Bayesian approach were adopted. In this article an objective Bayesian analysis is developed and illustrated on real and simulated data.     

Detection and Interpretation of a Multivariate Signal Using Combined Charts

A control procedure is presented in this article that is based on jointly using two separate control statistics in the detection and interpretation of signals in a multivariate normal process. The procedure detects the following three situations: (i) a mean vector shift without a shift in the covariance matrix; (ii) a shift in process variation (covariance matrix) without a mean vector shift; and (iii) both a simultaneous shift in the mean vector and covariance matrix as the result of a change in the parameters of some key process variables. It is shown that, following the occurrence of a signal on either of the separate control charts, the values from both of the corresponding signaling statistics can be decomposed into interpretable elements. Viewing the two decompositions together helps one to specifically identify the individual components and associated variables that are being affected. These components may include individual means or variances of the process variables as well as the correlations between or among variables. An industrial data set is used to illustrate the procedure.     

A generalization of Jeffreys' rule for non regular models

ABSTRACT

We propose a generalization of the one-dimensional Jeffreys' rule in order to obtain non informative prior distributions for non regular models, taking into account the comments made by Jeffreys in his article of 1946. These non informatives are parameterization invariant and the Bayesian intervals have good behavior in frequentist inference. In some important cases, we can generate non informative distributions for multi-parameter models with non regular parameters. In non regular models, the Bayesian method offers a satisfactory solution to the inference problem and also avoids the problem that the maximum likelihood estimator has with these models. Finally, we obtain non informative distributions in job-search and deterministic frontier production homogenous models.     

Empirical bayes interval estimates involving uniform distributions

Bayesian and empirical Bayesian decision rules are exhibited for the interval estimation of the parameter 0 of a Uniform (0,θ) distribution. The estimate ?,δ>resulting in the interval [?,?+δ]suffers loss given by L(?,δ>,θ)=1-[?≦e≦?+δ]+c₁((?-θ)²+(?+δ?θ)²))+c₂δ. The solution is presented for prior distributions G which have bounded support, no point masses,∫θ^?mdG(θ)<∞ and for some integer m. An example is presented involving a particular parametric form for G and rates of risk convergence in the empirical Bayes problem for this example are calculated.     

On the choice of co-ordinates in simultaneous estimation of normal means under misspecification of normal priors

The problem of choice of coordinates in Stein-type estimators,when simultaneously estimating normal means, is considered. The question of deciding whether to use all coordinates in one combined shrinkage estimators or to separate into groups and use separate shrinkage estimators on each group is considered in the situation in which part of the prior information may be " misspecified". It is observed that the amount of misspecification determines whether to use the combined shrinkage estimator the separate shrinkage estimator.