夏文化探索中的方法问题——"夏商周断代工程"结题后的反思(二)

目前,学术界公认中国历史上有个夏代。但由于文献记载太过简略,使后人对当时的社会历史状况知之甚少。在这种情况下,人们寄希望于考古工作者从地下找到夏代遗存。然而,在夏文化探索中,由于研究者的思路与所用方法不同,故而得出的结论也明显有异。由此,出现争论与分歧。于是,如何鉴别相关结论是否合理可信就成为学术界同人思索的问题。本文在对夏文化探索的现状进行回顾的基础上,围绕文化因素分析法与都城分析法,对分歧及其缘由作了详细探讨。文中还就坚持正确思路,采用科学方法。按科学规程操作对夏文化探索工作的重要性,谈了自己的看法。     

教育贷款审计的方法研究

高校扩招的压力迫使高等学校通过贷款来筹集资金进行基础设施建设,随之因贷款资金而产生的腐败、犯罪行为也在不断增加。论文通过分析贷款资金的来源和使用情况,揭示了教育贷款容易滋生腐败的薄弱环节,提出了建立教育贷款专项审计制度和内部控制审计为主的教育贷款审计的新审计思路和新方法。     

浅议法律解释中的利益衡量法

文章从法律解释与利益衡量的关系出发,阐明利益衡量在民事审判中是有其存在的必要的。并在此基础上,探讨了法官在进行利益衡量时应使用哪些方法,排除哪些有碍利益衡量的因素,以及进行利益衡量时应考虑的利益原则和所负担的相当注意义务。     

浅析袁隆平的科研方法

袁隆平是当代杰出的农业科学家,被国际同行誉为"杂交水稻之父".他在水稻杂交优势利用的开创和发展方面成就卓越.从科学方法而言,袁隆平院士在科研中成功运用了信息联想、辨证分析、试验探索、灵感思维等方法.     

农科博士生《植物分子生物学进展》课程教学方法的探讨

农科博士生《植物分子生物学进展》是一门旨在植物分子生物学领域提高博士生独立科研能力和开阔博士生科研视野的一门课程,本文从教学内容、考核方法、教学形式等三方面内容对该课程的教学方法进行了阐述和探讨。     

浅议普及图书检索知识的方法和途径

通过分析读者检索面临的问题及图书馆检索教育的不足,论述了检索知识普及的重要性与必要性,提出了对读者进行普及检索教育的方法与途径。     

On hysteretic vector autoregressive model with applications

This paper proposes a new hysteretic vector autoregressive (HVAR) model in which the regime switching may be delayed when the hysteresis variable lies in a hysteresis zone. We integrate an adapted multivariate Student-t distribution from amending the scale mixtures of normal distributions. This HVAR model allows for a higher degree of flexibility in the degrees of freedom for each time series. We use the proposed model to test for a causal relationship between any two target time series. Using posterior odds ratios, we overcome the limitations of the classical approach to multiple testing. Both simulated and real examples herein help illustrate the suggested methods. We apply the proposed HVAR model to investigate the causal relationship between the quarterly growth rates of gross domestic product of United Kingdom and United States. Moreover, we check the pairwise lagged dependence of daily PM2.5 levels in three districts of Taipei.     

Smoothed bootstrap bandwidth selection for nonparametric hazard rate estimation

A smoothed bootstrap method is presented for the purpose of bandwidth selection in nonparametric hazard rate estimation for iid data. In this context, two new bootstrap bandwidth selectors are established based on the exact expression of the bootstrap version of the mean integrated squared error of some approximations of the kernel hazard rate estimator. This is very useful since Monte Carlo approximation is no longer needed for the implementation of the two bootstrap selectors. A simulation study is carried out in order to show the empirical performance of the new bootstrap bandwidths and to compare them with other existing selectors. The methods are illustrated by applying them to a diabetes data set.     

Robust inference for estimating equations with nonignorably missing data based on SIR algorithm

Nonresponse is a very common phenomenon in survey sampling. Nonignorable nonresponse – that is, a response mechanism that depends on the values of the variable having nonresponse – is the most difficult type of nonresponse to handle. This article develops a robust estimation approach to estimating equations (EEs) by incorporating the modelling of nonignorably missing data, the generalized method of moments (GMM) method and the imputation of EEs via the observed data rather than the imputed missing values when some responses are subject to nonignorably missingness. Based on a particular semiparametric logistic model for nonignorable missing response, this paper proposes the modified EEs to calculate the conditional expectation under nonignorably missing data. We can apply the GMM to infer the parameters. The advantage of our method is that it replaces the non-parametric kernel-smoothing with a parametric sampling importance resampling (SIR) procedure to avoid nonparametric kernel-smoothing problems with high dimensional covariates. The proposed method is shown to be more robust than some current approaches by the simulations.     

Conditional design of the EWMA median chart with estimated parameters

The exponentially weighted moving average (EWMA) chart is often designed assuming the process parameters are known. In practice, the parameters are rarely known and need to be estimated from Phase I samples. Different Phase I samples are used when practitioners construct their own control chart's limits, which leads to the “Phase I between-practitioners” variability in the in-control average run length (ARL) of control charts. The standard deviation of the ARL (SDARL) is a good alternative to quantify this variability in control charts. Based on the SDARL metric, the performance of the EWMA median chart with estimated parameters is investigated in this paper. Some recommendations are given based on the SDARL metric. The results show that the EWMA median chart requires a much larger amount of Phase I data in order to reduce the variation in the in-control ARL up to a reasonable level. Due to the limitation of the amount of the Phase I data, the suggested EWMA median chart is designed with the bootstrap method which provides a good balance between the in-control and out-of-control ARL values.