ELICITING A DIRECTED ACYCLIC GRAPH FOR A MULTIVARIATE TIME SERIES OF VEHICLE COUNTS IN A TRAFFIC NETWORK

The problem of modelling multivariate time series of vehicle counts in traffic networks is considered. It is proposed to use a model called the linear multiregression dynamic model (LMDM). The LMDM is a multivariate Bayesian dynamic model which uses any conditional independence and causal structure across the time series to break down the complex multivariate model into simpler univariate dynamic linear models. The conditional independence and causal structure in the time series can be represented by a directed acyclic graph (DAG). The DAG not only gives a useful pictorial representation of the multivariate structure, but it is also used to build the LMDM. Therefore, eliciting a DAG which gives a realistic representation of the series is a crucial part of the modelling process. A DAG is elicited for the multivariate time series of hourly vehicle counts at the junction of three major roads in the UK. A flow diagram is introduced to give a pictorial representation of the possible vehicle routes through the network. It is shown how this flow diagram, together with a map of the network, can suggest a DAG for the time series suitable for use with an LMDM.     

没有场的空间是不存在的——广义相对论的空间概念

本文简述了空间概念的发展历程。经典力学和SR把空间看作虚无,而GR则认为空间是 物质的。从而指出了空间概念是人类思维的自由创造。     

新城市社会学视域下我国当代城市空间生产的特征

以新城市社会学理论的新马克思主义政治经济学来分析我国当代城市空间生产的特征,是一个新的视域。转型时期我国当代城市的空间生产呈现出新的特征,表现为资本、技术——工业理性刺激着城市的快速扩张,出现环境污染、建设破坏、文化破坏等社会问题,城市空间的生产是不同社会群体对空间的角逐过程和结果,反映着政府、公共领域与个人的边界。城市空间的生产能动地、全面地反映着资本、权力、财富、社会地位、利益等社会关系的生产。     

A Sparse Implementation of the Average Information Algorithm for Factor Analytic and Reduced Rank Variance Models

Factor analytic variance models have been widely considered for the analysis of multivariate data particularly in the psychometrics area. Recently Smith, Cullis & Thompson (2001) have considered their use in the analysis of multi‐environment data arising from plant improvement programs. For these data, the size of the problem and the complexity of the variance models chosen to account for spatial heterogeneity within trials implies that standard algorithms for fitting factor analytic models can be computationally expensive. This paper presents a sparse implementation of the average information algorithm (Gilmour, Thompson & Cullis, 1995) for fitting factor analytic and reduced rank variance models.     

Some results on optimality in models with heteroscedastic errors from partial optimum designs

This paper studies optimum designs for linear models when the errors are heteroscedastic. Sufficient conditions are given in order to obtainD-, A- andE-optimum designs for a complete regression model from partial optimum designs for some sub-parameters. A result about optimality for a complete model from the optimality for the submodels is included. Supported by Junta de Andalucía, research group FQM244.     

Block external bootstrap in partially linear models with nonstationary strong mixing error terms

The authors extend the block external bootstrap to partially linear regression models with strongly mixing, nonstationary error terms. In addition to providing an approximate distribution for the semiparametric least square estimator of the parametric component, they propose a consistent estimator of the co‐variance matrix of this estimator.     

Human Salmonellosis: Estimation of Dose-Illness from Outbreak Data

The quantification of the relationship between the amount of microbial organisms ingested and a specific outcome such as infection, illness, or mortality is a key aspect of quantitative risk assessment. A main problem in determining such dose-response models is the availability of appropriate data. Human feeding trials have been criticized because only young healthy volunteers are selected to participate and low doses, as often occurring in real life, are typically not considered. Epidemiological outbreak data are considered to be more valuable, but are more subject to data uncertainty. In this article, we model the dose-illness relationship based on data of 20 Salmonella outbreaks, as discussed by the World Health Organization. In particular, we model the dose-illness relationship using generalized linear mixed models and fractional polynomials of dose. The fractional polynomial models are modified to satisfy the properties of different types of dose-illness models as proposed by Teunis et al . Within these models, differences in host susceptibility (susceptible versus normal population) are modeled as fixed effects whereas differences in serovar type and food matrix are modeled as random effects. In addition, two bootstrap procedures are presented. A first procedure accounts for stochastic variability whereas a second procedure accounts for both stochastic variability and data uncertainty. The analyses indicate that the susceptible population has a higher probability of illness at low dose levels when the combination pathogen-food matrix is extremely virulent and at high dose levels when the combination is less virulent. Furthermore, the analyses suggest that immunity exists in the normal population but not in the susceptible population.     

图的点星荫度

引入了图的点星荫度的概念,研究了一般图的点星荫度的上界,着重讨论了平面图和外平面图的点星荫度。     

Pluralism and Universality of Environmental Discourse: The Dilemma Between Damage Caused by the Japanese Macaque and its Protection

Abstract:  The subject of this paper is to describe the complexity of relations between man and wild monkeys, which causes difficulties in forming a social consensus related to their conservation and management. To present how the relations are in everyday life, and how they are simplified in universal discursive spaces, interviews and a questionnaire survey have been conducted. As a result, it is clarified that there are three kinds of discursive spaces, that of politics, natural science, and residents. People who share the land with wild monkeys have various terms and stories about their relations with monkeys. The monkeys have various values in the discourse of residents, including many troubles. The existence of monkeys is vivid and close, and can be described as "accessible" nature. However, in discussion of politics or natural sciences, there is less diversity in monkeys' values. In these discursive spaces, monkeys are described simply in the framework of "distant" nature, and wild monkey issues are constructed as a "pest animal issue". The simplified protocol between accessible and distant nature makes the wild monkey issues simple. And the attitudes of residents are shown as controversial through the contradiction between simple-complex issues. In conclusion, this contradiction cannot be solved only by filling the gap between accessible and distant nature with social consensus, but also by connecting the two and enhancing the dynamism of society as a whole.     

Pseudo–Modelling of Outliers for Estimation of Regression And Time Series Models

This paper documents situations where the variance inflation model for outliers has undesirable properties. The model is commonly used to accommodate outliers in a Bayesian analysis of regression and time series models. The alternative approach provided here does not suffer from these undesirable properties but gives inferences similar to those of the variance inflation model when this is appropriate. It can be used with regression, time series, and regression with correlated errors in a unified way, and adheres to the scientific principle that inference should be based on the data after obvious outliers have been discarded. Only one parameter is required for outliers; it is interpretable as the a priori willingness to remove observations from the analysis.