李觏与佛教

李觏佛教思想具有双重性，既有排佛的一面，也有容佛的一面。排佛主要表现在两个领域，一是以经济建设、财富积累和社会秩序为内容的物质领域，一是儒家礼治伦理领域；容佛主要表现在对佛教某些教义、佛教教化功能的肯定。李觏佛教思想的基本内容及其特点，是颇有启示的。     

论李觏的诗

李觏的志节与境况，决定了他的论诗主张，其诗按内容大致可分为六类：交游、时事、咏史、咏物、写景、咏怀。颇受皮日休、韩愈等人的影响，又有所不同，这种同与异和宋诗风貌的形成有密切关系。     

GMM tests for the Katz family of distributions

Generalized method of moments (GMM) is used to develop tests for discriminating discrete distributions among the two-parameter family of Katz distributions. Relationships involving moments are exploited to obtain identifying and over-identifying restrictions. The asymptotic relative efficiencies of tests based on GMM are analyzed using the local power approach and the approximate Bahadur efficiency. The paper also gives results of Monte Carlo experiments designed to check the validity of the theoretical findings and to shed light on the small sample properties of the proposed tests. Extensions of the results to compound Poisson alternative hypotheses are discussed.     

Robustness of a Class of Partial Diallel Cross Designs to the Unavailability of a Complete Block of Observations

Complete and partial diallel cross designs are examined as to their construction and robustness against the loss of a block of observations. A simple generalized inverse is found for the information matrix of the line effects, which allows evaluation of expressions for the variances of the line-effect differences with and without the missing block. A-efficiencies, based on average variances of the elementary contrasts of the line-effects, suggest that these designs are fairly robust. The loss of efficiency is generally less than 10%, but it is shown that specific comparisons might suffer a loss of efficiency of as much as 40%.     

Goodness of fit for the inverse Gaussian distribution

For testing the fit of the inverse Gaussian distribution with unknown parameters, the empirical distribution-function statistic A² is studied. Two procedures are followed in constructing the test statistic; they yield the same asymptotic distribution. In the first procedure the parameters in the distribution function are directly estimated, and in the second the distribution function is estimated by its Rao-Blackwell distribution estimator. A table is given for the asymptotic critical points of A². These are shown to depend only on the ratio of the unknown parameters. An analysis is provided of the effect of estimating the ratio to enter the table for A². This analysis enables the proposal of the complete operating procedure, which is sustained by a Monte Carlo study.     

A Bayesian method for classification and discrimination

We discuss Bayesian analyses of traditional normal-mixture models for classification and discrimination. The development involves application of an iterative resampling approach to Monte Carlo inference, commonly called Gibbs sampling, and demonstrates routine application. We stress the benefits of exact analyses over traditional classification and discrimination techniques, including the ease with which such analyses may be performed in a quite general setting, with possibly several normal-mixture components having different covariance matrices, the computation of exact posterior classification probabilities for observed data and for future cases to be classified, and posterior distributions for these probabilities that allow for assessment of second-level uncertainties in classification.     

Deconvolution with supersmooth distributions

Nonparametric deconvolution problems require one to recover an unknown density when the data are contaminated with errors. Optimal global rates of convergence are found under the weighted L_p-loss (1 ≤ p ≤ ∞). It appears that the optimal rates of convergence are extremely low for supersmooth error distributions. To resolve this difficulty, we examine how high the noise level can be for deconvolution to be feasible, and for the deconvolution estimate to be as good as the ordinary density estimate. It is shown that if the noise level is not too high, nonparametric Gaussian deconvolution can still be practical. Several simulation studies are also presented.     

多样性·批评性·学术性－评《文艺湘军百家文库·文艺评论方阵》

《文艺湘军百家文库·文艺评论方阵》及先此出版的《当代湖南文艺评论家选集》丛书,集中汇聚了湖南文学批评50年的主要成果,展示了老中青三代批评家的探寻的风姿。其主要特点突出地表现在异彩纷呈的多样性、真诚鲜明的批评性、科学严谨的学术性等方面。     

乐教与儒者的宗教情怀

乐教是理解儒家精神不可忽视的重要方面。乐教扎根于“亲亲”之情,具体体现为与“忧患意识”有别,而与“安”“乐”相协调一致的“怛”和“哀”“悲”之情。此情实质上是超越的天道内化为人的心性而落实下来的生命意义与价值得以呈现的方式。儒者虽深知人生之哀、悲,但以乐入手,解悟和转化现实的人生与宇宙,是一大特色。如此,宗教情怀转化为现实的人生关怀,成为特有的礼乐文明的核心内涵。     

A Comparison of Partially Adaptive and Reweighted Least Squares Estimation

The small sample performance of least median of squares, reweighted least squares, least squares, least absolute deviations, and three partially adaptive estimators are compared using Monte Carlo simulations. Two data problems are addressed in the paper: (1) data generated from non-normal error distributions and (2) contaminated data. Breakdown plots are used to investigate the sensitivity of partially adaptive estimators to data contamination relative to RLS. One partially adaptive estimator performs especially well when the errors are skewed, while another partially adaptive estimator and RLS perform particularly well when the errors are extremely leptokur-totic. In comparison with RLS, partially adaptive estimators are only moderately effective in resisting data contamination; however, they outperform least squares and least absolute deviation estimators.