唐朝在教育规划中存在的问题研究

许多学者认为在中国教育史上唐朝的教育非常繁荣,但实际上唐朝教育的＂繁荣＂只是统治者规划出来的繁荣,是纸面上的设想,而非生活中的实情。唐朝的教育规划不切实际,且没有稳定的经费保障机制;各种专科教育发展规模由于硬性的法律规定而受到限制;等级教育、教育特权阻碍着唐朝教育下移和发展;在唐朝教育的规模中,对地方教育重视不够。这些问题,造成唐朝教育＂繁荣＂的名不副实。     

阴山文化文献与研究概述

系统研究阴山文化首先需要理清阴山文化的文献基础及研究现状。地方史志是研究阴山文化的基础资料,但存在着历史和地域的局限性。研究内蒙古、蒙古族及北方少数民族、草原文化的著作,均包含有大量阴山历史文化的。内容,可列入阴山文化研究的成果之中。探讨阴山某个局部、某个专题、某个方面历史文化的论著近年陆续面世,但缺乏系统性。把阴山文化作为一个专门的学术研究课题从整体上进行全面深入的研究,应该说才刚刚起步,还有大量的工作需要我们去做。     

Putting place on the menu: The negotiation of locality in UK food tourism,from production to consumption

This paper uses a case study of tourism in the Lake District and Exmoor to explore the relationship between ‘local food’ and sustainable rural tourism in the UK. Drawing on qualitative interviews with tourists, food producers and café, pub and restaurant owners, I use an approach based upon the commodity chain to trace the shifts in the discursive and material understandings of the ‘local’ that take place throughout the tourist food chain. These shifts are shown to occur in response to the need to negotiate the tensions between the ideals and the practicalities of food production and consumption which occur as a result of the relationships that exist throughout the food chain. Such conclusions are shown to be important for our understanding of the links between ‘local food’ and sustainable rural tourism because they indicate that we must attend to the values, as well as the practicalities, that drive the contemporary food sector at all stages of the food chain, from production to consumption.     

崇文向学与尚武好斗——明清历修《赣州府志》对赣南民风的表达

民风是各类地方志都会涉及到的普遍话题.在明清历修<赣州府志>中,崇文向学与尚武好斗是两幅主要的民风图景,这两幅图景既是地方志作者对赣南民风已然世界的白描,也是对赣南民风应然世界的期待.地方志对民风描写及诠释的微妙变化,既映射出地方社会治乱环境的变迁,更标示着国家与地方、地方与地方、精英与民众以及土著与移民之间的诸多权力关系和利益诉求,具有多元话语的特征.正是这一特征,规限着地方志在对地方民风做某种程度客观呈现的同时,又要做符合特定利益关系的建构.     

Optimal designs for tumor regrowth models

Most growth curves can only be used to model the tumor growth under no intervention. To model the growth curves for treated tumor, both the growth delay due to the treatment and the regrowth of the tumor after the treatment need to be taken into account. In this paper, we consider two tumor regrowth models and determine the locally D- and c-optimal designs for these models. We then show that the locally D- and c-optimal designs are minimally supported. We also consider two equally spaced designs as alternative designs and evaluate their efficiencies.     

Efficient Estimation of an Additive Quantile Regression Model

Abstract. In this paper, two non‐parametric estimators are proposed for estimating the components of an additive quantile regression model. The first estimator is a computationally convenient approach which can be viewed as a more viable alternative to existing kernel‐based approaches. The second estimator involves sequential fitting by univariate local polynomial quantile regressions for each additive component with the other additive components replaced by the corresponding estimates from the first estimator. The purpose of the extra local averaging is to reduce the variance of the first estimator. We show that the second estimator achieves oracle efficiency in the sense that each estimated additive component has the same variance as in the case when all other additive components were known. Asymptotic properties are derived for both estimators under dependent processes that are strictly stationary and absolutely regular. We also provide a demonstrative empirical application of additive quantile models to ambulance travel times.     

Non Null Asymptotic Distributions of Some Criteria in Censored Exponential Regression

In this article, we consider the class of censored exponential regression models which is very useful for modeling lifetime data. Under a sequence of Pitman alternatives, the asymptotic expansions up to order n^{? 1/2} of the non null distribution functions of the likelihood ratio, Wald, Rao score, and gradient statistics are derive in this class of models. The non null asymptotic distribution functions of these statistics are obtained for testing a composite null hypothesis in the presence of nuisance parameters. The power of all four tests, which are equivalent to first order, are compared based on these non null asymptotic expansions. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, we consider Monte Carlo simulations. We also present an empirical application for illustrative purposes.     

Local Influence Analysis for The Ridge Regression Under Stochastic Linear Restrictions

In this article, we assess the local influence for the ridge regression of linear models with stochastic linear restrictions in the spirit of Cook by using the log-likelihood of the stochastic restricted ridge regression estimator. The diagnostics under the perturbations of constant variance, responses and individual explanatory variables are derived. We also assess the local influence of the stochastic restricted ridge regression estimator under the approach suggested by Billor and Loynes. At the end, a numerical example on the Longley data is given to illustrate the theoretic results.     

Inference in segmented line regression: a simulation study

A segmented line regression model has been used to describe changes in cancer incidence and mortality trends [Kim, H.-J., Fay, M.P., Feuer, E.J. and Midthune, D.N., 2000, Permutation tests for joinpoint regression with applications to cancer rates. Statistics in Medicine, 19, 335–351. Kim, H.-J., Fay, M.P., Yu, B., Barrett., M.J. and Feuer, E.J., 2004, Comparability of segmented line regression models. Biometrics, 60, 1005–1014.]. The least squares fit can be obtained by using either the grid search method proposed by Lerman [Lerman, P.M., 1980, Fitting segmented regression models by grid search. Applied Statistics, 29, 77–84.] which is implemented in Joinpoint 3.0 available at http://srab.cancer.gov/joinpoint/index.html, or by using the continuous fitting algorithm proposed by Hudson [Hudson, D.J., 1966, Fitting segmented curves whose join points have to be estimated. Journal of the American Statistical Association, 61, 1097–1129.] which will be implemented in the next version of Joinpoint software. Following the least squares fitting of the model, inference on the parameters can be pursued by using the asymptotic results of Hinkley [Hinkley, D.V., 1971, Inference in two-phase regression. Journal of the American Statistical Association, 66, 736–743.] and Feder [Feder, P.I., 1975a, On asymptotic distribution theory in segmented regression Problems-Identified Case. The Annals of Statistics, 3, 49–83.] Feder [Feder, P.I., 1975b, The log likelihood ratio in segmented regression. The Annals of Statistics, 3, 84–97.] Via simulations, this paper empirically examines small sample behavior of these asymptotic results, studies how the two fitting methods, the grid search and the Hudson's algorithm affect these inferential procedures, and also assesses the robustness of the asymptotic inferential procedures.     

Estimating and testing effect size from an arbitrary population

In this article, we develop inference tools for an effect size parameter in a paired experiment. A class of estimators is defined that includes natural, shrinkage and shrinkage preliminary test estimators. The shrinkage and preliminary test methods incorporate uncertain prior information on the parameter. This information may be available in the form of a realistic guess on the basis of the experimenter’s knowledge and experience, which can be incorporated into the estimation process to increase the efficiency of the estimator. Asymptotic properties of the proposed estimators are investigated both analytically and computationally. A simulation study is also conducted to assess the performance of the estimators for moderate and large samples. For illustration purposes, the method is applied to a data set.