货车转向架参数化设计系统的开发

文章将参数化设计技术应用于货车转向架的设计,以Pro/Engineer为设计开发平台,以VisualC++6.0为集成开发环境,研究开发了基于参数化设计技术的货车转向架设计系统。     

Semiparametric estimation and testing in a model of environmental regulation with adverse selection

We consider a principal–agent model of environmental regulation with adverse selection, where firms are regulated through contracts. We show how the model allows to recover information on structural cost parameters. We use a semiparametric method to estimate consistently such parameters without specifying the distribution of the agents private information. We also show how to check for the specification of the econometric model, as well as auxiliary parametric assumptions, by means of specification tests based on nonparametric estimation. Results are used to discuss a selection of economic issues related to environmental regulation.First version received: August 2002/Final version received: November 2003Previous versions of this work were presented at Seminaire INRA-IDEI, Toulouse, the conference on Applications of semiparametric methods for micro-data, Tilburg, and seminars at UC Berkeley, University of Wisconsin–Madison, CREST, and INRA-LEA. We are indebted to participants, and especially Michael Visser, for their comments. We thank two referees for helpful comments. Financial support from the Conseil Régional Midi-Pyrénées and from INRA is gratefully acknowledged.     

An Empirical Test of Environmental Kuznets Curve for Water Pollution

The Environmental Kuznets Curve (EKC) on water pollution was investigated with both semiparametric and parametric models using watershed level data for the state of Louisiana, USA. The parametric model indicated the turning points within the range $10241–$12993, $6636–$13877, and $6467–$12758 for nitrogen (N), phosphorus (P), and dissolved oxygen (DO), respectively. However, only the parameters associated with N EKC were found to be significant. Model specification tests rejected parametric models in favor of semiparametric specification for P but not for N and DO.     

整体壁板参数化设计与敏感性分析

对整体壁板的止裂特性和损伤容限性能进行了计算和分析．应用参数化有限元技术,得到该结构的蒙皮裂纹尖端应力强度因子,分析了凸台和筋条对结构止裂特性的影响;随后根据线弹性断裂力学理论,计算了结构的剩余强度,并分析了凸台和筋条的存在对结构剩余强度的影响．为了分析结构几何参数对该结构的敏感性,给出了不同结构参数下的应力强度因子曲线,和其相对应的结构剩余强度曲线．这些曲线对整体壁板的结构设计提供了有意义的参考．     

Robust prediction of domain compositions from uncertain data using isometric logratio transformations in a penalized multivariate Fay–Herriot model

Assessing regional population compositions is an important task in many research fields. Small area estimation with generalized linear mixed models marks a powerful tool for this purpose. However, the method has limitations in practice. When the data are subject to measurement errors, small area models produce inefficient or biased results since they cannot account for data uncertainty. This is particularly problematic for composition prediction, since generalized linear mixed models often rely on approximate likelihood inference. Obtained predictions are not reliable. We propose a robust multivariate Fay–Herriot model to solve these issues. It combines compositional data analysis with robust optimization theory. The nonlinear estimation of compositions is restated as a linear problem through isometric logratio transformations. Robust model parameter estimation is performed via penalized maximum likelihood. A robust best predictor is derived. Simulations are conducted to demonstrate the effectiveness of the approach. An application to alcohol consumption in Germany is provided.     

Adjusting for Non‐Response in Population‐Based Case‐Control Studies

In this paper we discuss the analysis of data from population‐based case‐control studies when there is appreciable non‐response. We develop a class of estimating equations that are relatively easy to implement. For some important special cases, we also provide efficient semi‐parametric maximum‐likelihood methods. We compare the methods in a simulation study based on data from the Women's Cardiovascular Health Study discussed in Arbogast et al. (Estimating incidence rates from population‐based case‐control studies in the presence of non‐respondents, Biometrical Journal 44, 227–239, 2002).     

Misspecification Preferred: The Sensitivity of Inefficiency Rankings

Ruggiero (European Journal of Operational Research 115, 555–563. 1999) compared the two popular parametric frontier methods for cross-sectional data—the stochastic frontier and the corrected OLS—in a simulation study. He demonstrated that the inefficiency ranking accuracy of the established stochastic frontier is uniformly inferior to that of the misspecified Corrected OLS (COLS) (which lacks an error term). The reason for his result remains unclear, however. In this paper, a more extensive simulation study is therefore conducted to find out whether the superiority of COLS is simply due to small sample sizes or to poor performance of the inefficiency level estimator.JEL Classification: C1,C2,C5     

基于参数法的物流园区用地规模预测——以长沙市为例

随着物流业的快速发展,物流园区在各地蓬勃兴起。然而,我国物流园区开发建设在取得较大成功的同时,也存在规划上贪大求全、土地资源浪费、园区闲置率高等问题。以长沙为例,利用参数法预测长沙未来物流园区用地规模,可为物流园区用地规模预测提供参考。     

On Pooling of Data and Its Relative Efficiency

Pooling of data is often carried out to protect privacy or to save cost, with the claimed advantage that it does not lead to much loss of efficiency. We argue that this does not give the complete picture as the estimation of different parameters is affected to different degrees by pooling. We establish a ladder of efficiency loss for estimating the mean, variance, skewness and kurtosis, and more generally multivariate joint cumulants, in powers of the pool size. The asymptotic efficiency of the pooled data non‐parametric/parametric maximum likelihood estimator relative to the corresponding unpooled data estimator is reduced by a factor equal to the pool size whenever the order of the cumulant to be estimated is increased by one. The implications of this result are demonstrated in case–control genetic association studies with interactions between genes. Our findings provide a guideline for the discriminate use of data pooling in practice and the assessment of its relative efficiency. As exact maximum likelihood estimates are difficult to obtain if the pool size is large, we address briefly how to obtain computationally efficient estimates from pooled data and suggest Gaussian estimation and non‐parametric maximum likelihood as two feasible methods.     

A comment on Mendeş and Yiğit (2013), ‘Type I error and test power of different tests for testing interaction effects in factorial experiments’, Statistica Neerlandica, 67:1–26

In their advocacy of the rank‐transformation (RT) technique for analysis of data from factorial designs, Mende? and Yi?it (Statistica Neerlandica, 67, 2013, 1–26) missed important analytical studies identifying the statistical shortcomings of the RT technique, the recommendation that the RT technique not be used, and important advances that have been made for properly analyzing data in a non‐parametric setting. Applied data analysts are at risk of being misled by Mende? and Yi?it, when statistically sound techniques are available for the proper non‐parametric analysis of data from factorial designs. The appropriate methods express hypotheses in terms of normalized distribution functions, and the test statistics account for variance heterogeneity.