科学发展观——中国特色社会主义建设的指导思想

科学发展观是国际社会发展观的合理内核与中国实践发展的有机结合，是马克思主义中国化的最新成果，是中国特色的发展观，它创造性地回答了为什么发展、为谁发展、怎样发展的重大问题，是解决中国政治经济社会发展中各种矛盾问题所必须遵循的基本原则，是推进中国特色社会主义建设事业的所必须长期坚持的指导思想。     

A note on interval‐censored lifetime data and the constant‐sum condition of oiler,gómez & calle (2004)

Oiler, Gomez & Calle (2004) give a constant sum condition for processes that generate interval‐censored lifetime data. They show that in models satisfying this condition, it is possible to estimate non‐parametrically the lifetime distribution based on a well‐known simplified likelihood. The author shows that this constant‐sum condition is equivalent to the existence of an observation process that is independent of lifetimes and which gives the same probability distribution for the observed data as the underlying true process.     

A theoretical basis for perturbation methods

In this paper we discuss a new theoretical basis for perturbation methods. In developing this new theoretical basis, we define the ideal measures of data utility and disclosure risk. Maximum data utility is achieved when the statistical characteristics of the perturbed data are the same as that of the original data. Disclosure risk is minimized if providing users with microdata access does not result in any additional information. We show that when the perturbed values of the confidential variables are generated as independent realizations from the distribution of the confidential variables conditioned on the non-confidential variables, they satisfy the data utility and disclosure risk requirements. We also discuss the relationship between the theoretical basis and some commonly used methods for generating perturbed values of confidential numerical variables.     

COMPARISONS AND SELECTION OF TWO-PARAMETER EXPONENTIAL POPULATIONS

For two-parameter exponential populations with the same scale parameter (known or unknown) comparisons are made between the location parameters. This is done by constructing confidence intervals, which can then be used for selection procedures. Comparisons are made with a control, and with the (unknown) “best” or “worst” population. Emphasis is laid on finding approximations to the confidence so that calculations are simple and tables are not necessary. (Since we consider unequal sample sizes, tables for exact values would need to be extensive.)     

Local spatial data infrastructure, Trujillo-Peru

The development of a Municipal Information System, or currently better known as a local spatial data infrastructure, is considered complex due to the required inter-institutional relationships. In many developing countries Geographical Information Systems (GISs) are introduced but the benefits are modest as no changes take place in technical and organisational structure of organisations. Digital databases and computer-aided design (CAD) maps are mushrooming in great variety within different private and public institutions, municipal organisations and even within single departments and with structures similar to the paper period and thus operating on a stand-alone basis.Many national mapping agencies are not able to provide large-scale digital urban base maps, while the absence or low quality of cadastres makes those basic core data sets unavailable or inaccessible. The result is that duplication and incompatible data are frequently observed and also donor-driven stand-alone projects have a limited impact through the lack of institutional embedding and are not able to mature from the project to the institutional level. However, a positive sign is that there is an increasing awareness among data producers and consumers that investments in the development of digital data sets should be combined to reduce costs and increase benefits from especially GIS, and information and communication technology (ICT) in general.Within Trujillo a long-term vision was developed to make full use of ICT and GIS to modernise all operations of the Municipality to increase the efficiency and effectiveness of its tasks. However, large investments are not feasible due to the very limited municipal budgets. To guarantee the support of the municipal council, short-term results are required. This paper describes three ‘products’ as part of the vision to develop through a step-by-step approach a local spatial data infrastructure for Trujillo.The three, rather different, products are:

1. fiscal cadastre, to increase municipal revenues through property taxation;

2. an ‘environmental atlas’ based on a compatible spatial and attribute data sets from a variety of organisations; and

3. a municipal website with interactive GIS and meta data information.

The paper concludes with some comments on the institutional and political requirements for the successful development of a local spatial data infrastructure and stresses that such an infrastructure is not a product but an incremental development process that will progress only in case such a process is simple, cost effective, user-friendly, and flexible with clear products.Political interest and institutional stability and genuine interest for inter-institutional cooperation will add much to the success of this process.     

Multiple imputation of missing data with ante-dependence covariance structure

A controlled clinical trial was conducted to investigate the efficacy effect of a chemical compound in the treatment of Premenstrual Dysphoric Disorder (PMDD). The data from the trial showed a non-monotone pattern of missing data and an ante-dependence covariance structure. A new analytical method for imputing the missing data with the ante-dependence covariance is proposed. The PMDD data are analysed by the non-imputation method and two imputation methods: the proposed method and the MCMC method.     

Fuzzy K-means clustering models for triangular fuzzy time trajectories

We focus our attention on the classification of fuzzy time trajectories with triangular membership function, described by a given set of individuals. To this purpose, we adopt a fullyinformational approach, explicitly recognizing the informational nature shared by the ingredients of the classification procedure: the observed data (Empirical Information) and the classification model (Theoretical Information). In particular, by supposing that the informational paradigm has a fuzzy nature, we suggest three fuzzy clustering models allowing the classification of the triangular fuzzy time trajectories, based on the analysis of the cross sectional and/or longitudinal characteristics of their components (centers and spreads). Two applicative examples are illustrated.     

Residual analysis for spatial point processes (with discussion)

Summary.  We define residuals for point process models fitted to spatial point pattern data, and we propose diagnostic plots based on them. The residuals apply to any point process model that has a conditional intensity; the model may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Some existing ad hoc methods for model checking (quadrat counts, scan statistic, kernel smoothed intensity and Berman's diagnostic) are recovered as special cases. Diagnostic tools are developed systematically, by using an analogy between our spatial residuals and the usual residuals for (non-spatial) generalized linear models. The conditional intensity λ plays the role of the mean response. This makes it possible to adapt existing knowledge about model validation for generalized linear models to the spatial point process context, giving recommendations for diagnostic plots. A plot of smoothed residuals against spatial location, or against a spatial covariate, is effective in diagnosing spatial trend or co-variate effects. Q – Q -plots of the residuals are effective in diagnosing interpoint interaction.     

Asymptotic bias in the linear mixed effects model under non-ignorable missing data mechanisms

Summary.  In longitudinal studies, missingness of data is often an unavoidable problem. Estimators from the linear mixed effects model assume that missing data are missing at random. However, estimators are biased when this assumption is not met. In the paper, theoretical results for the asymptotic bias are established under non-ignorable drop-out, drop-in and other missing data patterns. The asymptotic bias is large when the drop-out subjects have only one or no observation, especially for slope-related parameters of the linear mixed effects model. In the drop-in case, intercept-related parameter estimators show substantial asymptotic bias when subjects enter late in the study. Eight other missing data patterns are considered and these produce asymptotic biases of a variety of magnitudes.     

Influence diagnostics and outlier tests for semiparametric mixed models

Summary. Semiparametric mixed models are useful in biometric and econometric applications, especially for longitudinal data. Maximum penalized likelihood estimators (MPLEs) have been shown to work well by Zhang and co-workers for both linear coefficients and nonparametric functions. This paper considers the role of influence diagnostics in the MPLE by extending the case deletion and subject deletion analysis of linear models to accommodate the inclusion of a nonparametric component. We focus on influence measures for the fixed effects and provide formulae that are analogous to those for simpler models and readily computable with the MPLE algorithm. We also establish an equivalence between the case or subject deletion model and a mean shift outlier model from which we derive tests for outliers. The influence diagnostics proposed are illustrated through a longitudinal hormone study on progesterone and a simulated example.