Sensitivity,uncertainty, and decision analyses in the prioritization of research

The evaluation of hazards from complex, large scale, technologically advanced systems often requires the construction of computer implemented mathematical models. These models are used to evaluate the safety of the systems and to evaluate the consequences of modifications to the systems. These evaluations, however, are normally surrounded by significant uncertainties related to the uncertainty inherent in natural phenomena such as the weather and those related to uncertainties in the parameters and models used in the evaluation.

Another use of these models is to evaluate strategies for improving information used in the modeling process itself. While sensitivity analysis is useful in defining variables in the model that are important, uncertainty analysis provides a tool for assessing the importance of uncertainty about these variables. A third complementary technique, is decision analysis. It provides a methodology for explicitly evaluating and ranking potential improvements to the model. Its use in the development of information gathering strategies for a nuclear waste repository are discussed in this paper.     

Fused least absolute shrinkage and selection operator for credit scoring

Credit scoring can be defined as the set of statistical models and techniques that help financial institutions in their credit decision makings. In this paper, we consider a coarse classification method based on fused least absolute shrinkage and selection operator (LASSO) penalization. By adopting fused LASSO, one can deal continuous as well as discrete variables in a unified framework. For computational efficiency, we develop a penalization path algorithm. Through numerical examples, we compare the performances of fused LASSO and LASSO with dummy variable coding.     

Moment‐Independent Sensitivity Analysis Using Copula

In risk assessment, the moment‐independent sensitivity analysis (SA) technique for reducing the model uncertainty has attracted a great deal of attention from analysts and practitioners. It aims at measuring the relative importance of an individual input, or a set of inputs, in determining the uncertainty of model output by looking at the entire distribution range of model output. In this article, along the lines of Plischke et al., we point out that the original moment‐independent SA index (also called delta index) can also be interpreted as the dependence measure between model output and input variables, and introduce another moment‐independent SA index (called extended delta index) based on copula. Then, nonparametric methods for estimating the delta and extended delta indices are proposed. Both methods need only a set of samples to compute all the indices; thus, they conquer the problem of the “curse of dimensionality.” At last, an analytical test example, a risk assessment model, and the levelE model are employed for comparing the delta and the extended delta indices and testing the two calculation methods. Results show that the delta and the extended delta indices produce the same importance ranking in these three test examples. It is also shown that these two proposed calculation methods dramatically reduce the computational burden.     

A new generalization of alpha-skew-normal distribution

In this paper, a new generalization of alpha-skew-normal distribution is considered. Some properties of this distribution, which is denoted by GASN(α, λ), including moments, maximum likelihood estimation of parameters, and some other properties are studied. Finally, using a real data set, we show that our new distribution is the best-fitted distribution for the used data among normal, skew normal, alpha-skew-normal, and skew-bimodal-normal distributions.     

动态性与静态性:教学目标的确定及实现——以“教育研究方法”课程为例

教学目标的存在有应然状态和实然状态之分。"教育研究方法"课程的静态目标应具体体现为"涵养科学精神、问题意识的形成、基本研究技能的掌握和有效获取文献信息",这些目标在实现过程中必然存在着动态性选择。     

漯河市新兴产业发展政策研究

近年来漯河大量承接产业转移,一些能源企业、电子信息技术企业、生物制药企业落户漯河。以这些企业为代表的新兴产业在漯河逐步兴起,因此,应从政策引导、规划设计、财政扶持和人才培养等政策层面鼓励和刺激新兴产业的崛起。     

全国及省际人力资本水平存量估算

估算全国和省际人力资本水平是经济增长研究所不能回避的问题。当前的研究主要采用教育年限法、物质投入法、生产函数法、人力资本回报法、人力资本特征与收入法和J-F终生收入法等六种方法。多角度比较和判别,可以验证生产函数法测算的各年相对人力资本水平较为可靠。使用生产函数法估算全国和各省的1952-2008年的人力资本存量,可刻画统一单位衡量的全国和各省人力资本水平。总体来说,全国和各省人力资本水平呈增长状态,各省人力资本存量以及增长速度存在明显差异。     

Asymptotic relative efficiency of the linear discriminant function under partial nonrandom classification of the training data

This paper considers the problem where the linear discriminant rule is formed from training data that are only partially classified with respect to the two groups of origin. A further complication is that the data of unknown origin do not constitute an observed random sample from a mixture of the two under- lying groups. Under the assumption of a homoscedastic normal model, the overall error rate of the sample linear discriminant rule formed by maximum likelihood from the partially classified training data is derived up to and including terms of the first order in the case of univariate feature data. This first- order expansion of the sample rule so formed is used to define its asymptotic efficiency relative to the rule formed from a completely classified random training set and also to the rule formed from a completely unclassified random set.     

房屋拆迁中的国有土地使用权补偿司法实证研究

房屋拆迁中的国有土地使用权补偿是我国城镇房屋拆迁中的主要矛盾点之一。通过对司法判例进行实证研究发现，法院判决多数认为原告诉请国有土地使用权补偿于法无据，抑或认为对于国有土地使用权的补偿已随房屋评估作价。房屋拆迁的重点在于“地”，若仅对房屋所有权人进行补偿，而忽视国有土地使用权人，无疑会引发诸多诉讼，乃至于阻碍城镇化进程。因此，在渐进式改革的背景之下，可以开展国有土地使用权补偿的试点，同时应当完善《国有土地上房屋征收与补偿条例》，并将合理补偿原则作为补偿的基本原则，以此为基础建立一套独立于房屋拆迁补偿的国有土地使用权补偿体系。     

The empirical Bayes estimators of the parameter of the Poisson distribution with a conjugate gamma prior under Stein's loss function

For the hierarchical Poisson and gamma model, we calculate the Bayes posterior estimator of the parameter of the Poisson distribution under Stein's loss function which penalizes gross overestimation and gross underestimation equally and the corresponding Posterior Expected Stein's Loss (PESL). We also obtain the Bayes posterior estimator of the parameter under the squared error loss and the corresponding PESL. Moreover, we obtain the empirical Bayes estimators of the parameter of the Poisson distribution with a conjugate gamma prior by two methods. In numerical simulations, we have illustrated: The two inequalities of the Bayes posterior estimators and the PESLs; the moment estimators and the Maximum Likelihood Estimators (MLEs) are consistent estimators of the hyperparameters; the goodness-of-fit of the model to the simulated data. The numerical results indicate that the MLEs are better than the moment estimators when estimating the hyperparameters. Finally, we exploit the attendance data on 314 high school juniors from two urban high schools to illustrate our theoretical studies.