独立学院的诞生与发展态势研究

从客观公正的视角,以统计数据为依据,揭示了独立学院诞生的原因是在高等教育大众化和企业不景气的环境下高等教育供需不均衡,指出了独立学院在地域分布上的基本均衡性及其与地区经济和高校规模的显著相关性。通过与普通高校对比发现,独立学院的学科结构具有相似性,对应用性工科人才和财经类人才的大力培养符合社会的需求。通过与教育部直属高校和普通民办高校对比发现,独立学院与民办高校都缺乏较高水平专任师资,但管理人员所占比例显著少于教育部直属高校。结合母体高校办学水平和校友会网的评价还发现,211工程大学申办的独立学院办学水平普遍好于其他独立学院。     

数字在汉诗中的意境效果

数字用于诗中,表示松散的用法,对创造特别的意境效果具有以下作用：提供恰当、宽泛的语境,给百科条目搜索指引方向;创造鲜明的印象、优美的意境,给读者以美的享受和体验;创造特别语境效果,调动读者情感,引起读者与作者感情的共鸣。分析数字在诗中所创造的意境效果,使我们对数字在语言使用中的表现力和重要性有更深刻的认识。     

On the power of some tests for examining the stability of regression coefficients

The main objective of the study is to compare four different procedures to test for the stability of regression coefficients. The comparisons are based on a numerical study and are with respect to their abilities to detect various simple forms of parameter instabilities. Besides the power comparisons a special interest is directed towards the choice of “window length” in the tests based on moving sums of squared recursive and ordinary least-squares residuals.     

Sampling methods and sensitivity analysis for large parameter sets

Models with large parameter (i.e., hundreds or thousands of parameters) often behave as if they depend upon only a few parameters, with the rest having comparatively little influence. One challenge of sensitivity analysis with such models is screening parameters to identify the influential ones, and then characterizing their influences.

Large models often require significant computing resources to evaluate their output, and so a good screening mechanism should be efficient: it should minimize the number of times a model must be exercised. This paper describes an efficient procedure to perform sensitivity analysis on deterministic models with specified ranges or probability distributions for each parameter.

It is based on repeated exercising of the model, which can be treated as a black box. Statistical checks can ensure that the screening identified parameters that account for the bulk of the model variation. Subsequent sensitivity analysis can use the screening information to reduce the investment required to characterize the influence of influential and other parameters.

The procedure exploits simplifications in the dependence of a model output on model inputs. It works best where a small number of parameters are much more influential than all the rest. The method is much more sensitive to the number of influential parameters than to the total number of parameters. It is most effective when linear or quadratic effects dominate higher order effects and complex interactions.

The paper presents a set of M athematica functions that can be used to create a variety of types of experimental designs useful for sensitivity analysis, including simple random, latin hypercube and fractional factorial sampling. Each sampling method can use discretization, folding, grouping and replication to create composite designs. These techniques have beencombined in a composite approach called Iterated Fractional Factorial Design (IFFD).

The procedure is applied to model of nuclear fuel waste disposal, and to simplified example models to demonstrate the concepts involved.     

On the inadmssibelity of ridge estimator in a linear model

The necessary and sufficient conditions for the inadmissibility of the ridge regression is discussed under two different criteria, namely, average loss and Pitman nearness. Although the two criteria are very different, same conclusions are obtained. The loss functions considered in this article are th likelihood loss function and the Mahalanobis loss function. The two loss functions are motivated from the point of view of classification of two normal populations. Under the Mahalanobis loss it is demonstrated that the ridge regression is always inadmissible as long as the errors are assumed to be symmetrically distributed about the origin.     

Model Averaging Using Fractional Polynomials to Estimate a Safe Level of Exposure

Quantitative risk assessment involves the determination of a safe level of exposure. Recent techniques use the estimated dose-response curve to estimate such a safe dose level. Although such methods have attractive features, a low-dose extrapolation is highly dependent on the model choice. Fractional polynomials, basically being a set of (generalized) linear models, are a nice extension of classical polynomials, providing the necessary flexibility to estimate the dose-response curve. Typically, one selects the best-fitting model in this set of polynomials and proceeds as if no model selection were carried out. We show that model averaging using a set of fractional polynomials reduces bias and has better precision in estimating a safe level of exposure (say, the benchmark dose), as compared to an estimator from the selected best model. To estimate a lower limit of this benchmark dose, an approximation of the variance of the model-averaged estimator, as proposed by Burnham and Anderson, can be used. However, this is a conservative method, often resulting in unrealistically low safe doses. Therefore, a bootstrap-based method to more accurately estimate the variance of the model averaged parameter is proposed.     

从“个人自主活动”视角看《德意志意识形态》的逻辑问题

《德意志意识形态》作为马克思恩格斯新历史观和新唯物主义形成的重要标志,具有重大的理论和历史意义。本文从"个人自主活动"的视角出发,从整体的逻辑框架来审视《形态》全篇文章,却发现了《形态》在两个方面存在着逻辑论证的缺憾。一方面,《形态》在论述私有制的时候,认定私有制的不完全状态决定了社会不可能形成统治者和非统治者两大集团,而在论述"自主性"的时候,却实际上利用了统治者和非统治者者两大集团来论述大工业和普遍竞争之前的个人自主活动。另一方面,《形态》在"人"的概念上,以"无产阶级"现实群体概念代替了"个人"的马克思的整个历史发展学说的人的"个体"概念,却没有给予恰当的说明。     

A Bayesian estimation of lag lengths in distributed lag models

Dynamic regression models are widely used because they express and model the behaviour of a system over time. In this article, two dynamic regression models, the distributed lag (DL) model and the autoregressive distributed lag model, are evaluated focusing on their lag lengths. From a classical statistics point of view, there are various methods to determine the number of lags, but none of them are the best in all situations. This is a serious issue since wrong choices will provide bad estimates for the effects of the regressors on the response variable. We present an alternative for the aforementioned problems by considering a Bayesian approach. The posterior distributions of the numbers of lags are derived under an improper prior for the model parameters. The fractional Bayes factor technique [A. O'Hagan, Fractional Bayes factors for model comparison (with discussion), J. R. Statist. Soc. B 57 (1995), pp. 99–138] is used to handle the indeterminacy in the likelihood function caused by the improper prior. The zero-one loss function is used to penalize wrong decisions. A naive method using the specified maximum number of DLs is also presented. The proposed and the naive methods are verified using simulation data. The results are promising for the method we proposed. An illustrative example with a real data set is provided.     

Alternative beta estimation for the market model using partially adaptive techniques

The leptokurtosls of many security market return distributions can contaminate ordinary least squares estimates of the β coefficient of the market model. Partially adaptive estimation techniques accommodate the possibility of fat tailed distributions. this methodology limits the influence of extremely large residuals and yields estimates which are both statistically and practically different from ordinary least squares.     

地方普通高校四维生存力探析

地方普通高校对推进我国高等教育大众化进程功不可没，但内外在条件约束，主要在目前高等教育体系夹缝中求生存、谋发展，唯有构建以明道力、取势力、优术力、树人力为四维内涵的生存力，地方普通高校才能真正步人生存与发展正轨。