A Bayesian approach for improved pavement performance prediction

We present a method for predicting future pavement distresses such as longitudinal cracking. These predicted distress values are used to plan road repairs. Large inherent variability in measured cracking and an extremely small number of observations are the nature of the pavement cracking data, which calls for a parametric Bayesian approach. We model theoretical pavement distress with a sigmoidal equation with coefficients based on prior engineering knowledge. We show that a Bayesian formulation akin to Kalman filtering gives sensible predictions and provides defendable uncertainty statements for predictions. The method is demonstrated on data collected by the Texas Transportation Institute at several sites in Texas. The predictions behave in a reasonable and statistically valid manner.     

公路建筑业对国民经济相关产业的贡献研究

 本文以黑龙江省为例,依据2007年黑龙江省的投入产出表和抽样调查资料,把公路建筑业从建筑业中分离出来,编制了包含公路建筑业在内的七部门的投入产出表,并采用投入产出法分别测算了公路建筑业对国民经济相关产业的直接贡献和间接贡献,得出结论表明公路建筑业对国民经济相关产业的贡献主要来源于后向关联贡献值,说明公路建筑业会对其他产业部门有较强的带动作用,今后应进一步加大投入力度,大力发展公路建筑业。     

Self-starting X-bar control chart based on Six Sigma quality and sometimes pooling procedure

Self-starting control charts have been proposed in the literature to allow process monitoring when only a small amount of relevant data is available. In fact, self-starting charts are useful in monitoring a process quickly, without having to collect a sizable Phase I sample for estimating the in-control process parameters. In this paper, a new self-starting control charting procedure is proposed in which first an effective initial sample is chosen from the perspective of Six Sigma quality, then the successive sample means are either pooled or not pooled (sometimes pooling procedure) for computing next Q-statistics depending upon its signal. It is observed that the sample statistics obtained so from this in-control Phase I situation can serve as more efficient estimators of unknown parameters for Phase II monitoring. An example is considered to illustrate the construction of the proposed chart and to compare its performance with the existing ones.     

基础设施建设投资拉动经济增长预算研究

一、问题的提出基础设施有广义和狭义之分 ,狭义的基础设施只包含提供物质条件、工程设施和有形资产的部门和行业 ;广义的基础设施不仅包括有形的物质基础设施 ,还包括文化、教育、科学技术等无形资产的部分。基础设施对不同国家、地域或经济区域其含义也不相同。按照我国现行的经济管理体制和产业分类 ,本课题的研究范畴是指狭义的基础设施而言 ,主要包括公共设施及其产业部门 ,如电力、交通通讯、给排水、供气供热、卫生设施等 ;公共工程及其产业部门 ,如道路桥梁、大坝渠道等 ;其它城市设施及其产业部门 ,如城市间公路铁路、港口、机场等…     

Automating argument construction

Over the past five years the Artificial Intelligence Center at SRI has been developing a new technology to address the problem of automated information management within real- world contexts. The result of this work is a body of techniques for automated reasoning from evidence that we call evidential reasoning. The techniques are based upon the mathematics of belief functions developed by Dempster and Shafer and have been successfully applied to a variety of problems including computer vision, multisensor integration, and intelligence analysis.

We have developed both a formal basis and a framework for implementating automated reasoning systems based upon these techniques. Both the formal and practical approach can be divided into four parts: (1) specifying a set of distinct propositional spaces, (2) specifying the interrelationships among these spaces, (3) representing bodies of evidence as belief distributions, and (4) establishing paths of the bodies for evidence to move through these spaces by means of evidential operations, eventually converging on spaces where the target questions can be answered. These steps specify a means for arguing from multiple bodies of evidence toward a particular (probabilistic) conclusion. Argument construction is the process by which such evidential analyses are constructed and is the analogue of constructing proof trees in a logical context.

This technology features the ability to reason from uncertain, incomplete, and occasionally inaccurate information based upon seven evidential operations: fusion, discounting, translation, projection, summarization, interpretation, and gisting. These operation are theoretically sound but have intuitive appeal as well.

In implementing this formal approach, we have found that evidential arguments can be represented as graphs. To support the construction, modification, and interrogation of evidential arguments, we have developed Gister. Gister provides an interactive, menu-driven, graphical interface that allows these graphical structures to be easily manipulated.

Our goal is to provide effective automated aids to domain experts for argument construction. Gister represents our first attempt at such an aid.     

Approximation spline de la prevision d'un processus fonctionnel autorégressif d'ordre 1

ABSTRACT We present a method to approximate and forecast, on an entire interval, a continuous-time process. For this purpose, we use the modelization of ARH(l) processes, defined by Bosq (1991). We deal with the practical problem of the discretization of the observed trajectories and approximate them by means of spline functions. We show by simulations that for well-chosen smoothing parameters, good prediction can be obtained in comparison with the “predictable” part of the process. Finally, we apply this model to forecast road traffic and compare it with a SARIMA model.     

Analysis of means approach for random factor analysis

Analysis of means (ANOM) is a powerful tool for comparing means and variances in fixed-effects models. The graphical exhibit of ANOM is considered as a great advantage because of its interpretability and its ability to evaluate the practical significance of the mean effects. However, the presence of random factors may be problematic for the ANOM method. In this paper, we propose an ANOM approach that can be applied to test random effects in many different balanced statistical models including fixed-, random- and mixed-effects models. The proposed approach utilizes the range of the treatment averages for identifying the dispersions of the underlying populations. The power performance of the proposed procedure is compared to the analysis of variance (ANOVA) approach in a wide range of situations via a Monte Carlo simulation study. Illustrative examples are used to demonstrate the usefulness of the proposed approach and its graphical exhibits, provide meaningful interpretations, and discuss the statistical and practical significance of factor effects.     

Constructing copula functions with weighted geometric means

The weighted arithmetic mean of two copulas is a copula. In some cases, geometric and harmonic means also provide copulas. There are copulas specially appropriate to be combined by using weighted geometric means. With this method of construction we combine Farlie–Gumbel–Morgentern and Ali–Mikhail–Haq copulas to obtain families of copulas which can be expressed in terms of double power series. The Gumbel–Barnett copula is also considered and a new copula is proposed, which arises as the first order approximation of the weighted geometric mean of two copulas. Invariance of two multivariate distributions (Cuadras–Augé and Johnson–Kotz) by weighted geometric and arithmetic means is also studied.     

基于大数据规则挖掘的交通拥堵治理研究

随着中国城市机动车保有量的急剧增多,交通拥堵已经成为现代城市病。交通拥堵在道路网络中呈现向四周放射的传导特性,拥堵路段倾向于将拥堵扩散传导到其他相邻路段,该特性此前未被系统研究过,综合比较各种方法的适用性,从时间和大数据规则挖掘角度对拥堵建模;使用时间序列规则挖掘算法建立交通拥堵传导规律模型,并基于传导规则预测未来交通流状况;更重要的是,挖掘出来的拥堵传导规则直观可用,能够用于建立拥堵预警防治机制,完善道路路网建设规划中不合理的部分,从而达到提升交通效率的目的。研究结果证明本模型能够较好达到研究目的,挖掘出的拥堵传导规则可以精确分析交通拥堵状况并预测未来交通流状况,因此可以为交通拥堵治理决策提供重要参考。     

On the α-risks for shewhart control charts

The performance of the usual Shewhart control charts for monitoring process means and variation can be greatly affected by nonnormal data or subgroups that are correlated. Define the α_k-risk for a Shewhart chart to be the probability that at least one “out-of-control” subgroup occurs in k subgroups when the control limits are calculated from the k subgroups. Simulation results show that the α_k-risks can be quite large even for a process with normally distributed, independent subgroups. When the data are nonnormal, it is shown that the α_k-risk increases dramatically. A method is also developed for simulating an “in-control” process with correlated subgroups from an autoregressive model. Simulations with this model indicate marked changes in the α_k-risks for the Shewhart charts utilizing this type of correlated process data. Therefore, in practice a process should be investigated thoroughly regarding whether or not it is generating normal, independent data before out-of-control points on the control charts are interpreted to be due to some real assignable cause.     

Graphical comparison of means with a standard in the one-way layout

Some simple test procedures are considered for comparing several group means with a standard value when the data are in a one-way layout. The underlying distributions are assumed to be normal with possibly unequal variances. The tests are based on a union-intersection formulation and can be applied in a form similar to a Shewhart control chart. Both two-sided and one-sided alternatives are considered. The power of the tests can be obtained from tables of a non-central t distribution. Implementation of the tests is illustrated with a numerical example. The tests help identify any group means different from the standard and might lead to a decision about rejecting the null hypothesis before all the group means are observed. The resulting savings in time and resources might be valuable in applications where the number of groups is large and the cost of acquiring data is high. For situations where the normality assumption is untenable, a non-parametric procedure, based on one-sample sign tests is considered.     

基于MixedLogit模型的道路交通统计生命价值评价研究

道路交通统计生命价值是道路交通安全项目经济评价的重要指标。运用意愿选择法和正交试验法设计了出行路径选择的调查问卷。假定时间、死亡风险为常数,费用服从对数正态分布,建立了基于Mixed Logit模型的统计生命价值评价模型。以大连市私家车出行者为调查对象获得调查数据,利用Monte Carlo方法并借助GAUSS软件对模型进行了150次仿真实验。研究表明：模型各参数的估计值具有较强集中性,t检验值具有较强显著性,模型优度比较高。统计生命价值服从参数为0．922和0．814的对数正态分布,其数学期望是35万元,可以作为道路交通安全项目经济评价的参考数据。     

Estimation of origin–destination trip rates in Leicester

The road system in region RA of Leicester has vehicle detectors embedded in many of the network's road links. Vehicle counts from these detectors can provide transportation researchers with a rich source of data. However, for many projects it is necessary for researchers to have an estimate of origin-to-destination vehicle flow rates. Obtaining such estimates from data observed on individual road links is a non-trivial statistical problem, made more difficult in the present context by non-negligible measurement errors in the vehicle counts collected. The paper uses road link traffic count data from April 1994 to estimate the origin–destination flow rates for region RA. A model for the error prone traffic counts is developed, but the resulting likelihood is not available in closed form. Nevertheless, it can be smoothly approximated by using Monte Carlo integration. The approximate likelihood is combined with prior information from a May 1991 survey in a Bayesian framework. The posterior is explored using the Hastings–Metropolis algorithm, since its normalizing constant is not available. Preliminary findings suggest that the data are overdispersed according to the original model. Results for a revised model indicate that a degree of overdispersion exists, but that the estimates of origin–destination flow rates are quite insensitive to the change in model specification.     

Mobile safety cameras: estimating casualty reductions and the demand for secondary healthcare

We consider a fully Bayesian analysis of road casualty data at 56 designated mobile safety camera sites in the Northumbria Police Force area in the UK. It is well documented that regression to the mean (RTM) can exaggerate the effectiveness of road safety measures and, since the 1980s, an empirical Bayes (EB) estimation framework has become the gold standard for separating real treatment effects from those of RTM. In this paper we suggest some diagnostics to check the assumptions underpinning the standard estimation framework. We also show that, relative to a fully Bayesian treatment, the EB method is over-optimistic when quantifying the variability of estimates of casualty frequency. Implementing a fully Bayesian analysis via Markov chain Monte Carlo also provides a more flexible and complete inferential procedure. We assess the sensitivity of estimates of treatment effectiveness, as well as the expected monetary value of prevention owing to the implementation of the safety cameras, to different model specifications, which include the estimation of trend and the construction of informative priors for some parameters.     

AFFINE‐EQUIVARIANT SPATIAL MEDIAN AND ITS USE IN THE MULTIVARIATE MULTI‐SAMPLE LOCATION PROBLEM

The classical spatial median is not affine‐equivariant, which often turns out to be an unfavourable property. In this paper, the asymptotic properties of an affine‐equivariant modification of the spatial median are investigated. It is shown that under some weak regularity conditions, the modified spatial median computed by means of the sample norming matrix is asymptotically equivalent to the one computed by means of the population norming matrix, which yields its asymptotic normality. A consistent estimate of the asymptotic covariance matrix of the modified spatial median is also presented. These results are implemented in a scheme, where the sample norm is determined by means of the sample Dümbgen scatter matrix. The results are utilized in the construction of affine‐invariant test statistics for testing the multi‐sample hypothesis of equality of location parameters. The performance of the proposed tests is demonstrated through a simulation study.     

Construction of Cross-Over Designs for Comparing Test Treatments with Control Using Terraces

Segregated half-and-half and mutually orthogonal power sequence terraces have been used in this article for the construction of some new families of control balanced cross-over designs, which are Schur-optimal. One of the advantages of using terraces is that designs with larger number of treatments can also be constructed with relative ease. Designs up to 17 treatments have been constructed in this article.     

Empirical likelihood confidence regions for comparison distributions and roc curves

Abstract: The authors derive empirical likelihood confidence regions for the comparison distribution of two populations whose distributions are to be tested for equality using random samples. Another application they consider is to ROC curves, which are used to compare measurements of a diagnostic test from two populations. The authors investigate the smoothed empirical likelihood method for estimation in this context, and empirical likelihood based confidence intervals are obtained by means of the Wilks theorem. A bootstrap approach allows for the construction of confidence bands. The method is illustrated with data analysis and a simulation study.     

INFLUENCE FUNCTIONS IN FUNCTIONAL MEASUREMENT ERROR MODELS WITH REPLICATED DATA

We consider the construction and properties of influence functions in the context of functional measurement error models with replicated data. In these models estimates of the parameters can be affected both by the individual observations and the means of replicated observations. We show that influence function of the means of replicates on the estimate of regression coefficients can be only derived under the assumption that the variances of the errors are known, while one for the individual observations can be only derived simultaneously with their influence function on the estimators of the variances of the errors.     

A multiple comparisons procedure for detecting differences between treatments and a control in two-factor experiments

In many experiments researchers are interested in comparing several treat¬ment means with a control mean. Their primary interest is to determine whether any treatments are significantly better than the control Several test procedures have been proposed in the literature, but only few of them can pro¬vide simultaneous confidence lower bounds. A new test statistic is proposed to compare treatment means with a control mean in two-factor experiments. Some upper percentage points are tabulated. It yields sharp simultaneous confidence lower bounds for the differences of such means. The new test is forresponding author.     

Interacting neighbour point processes: Some models for clustering

We introduce a class of spatial point processesinteracting neighbour point (INP) processes, where the density of the process can be written by means of local interactions between a point and subsets of its neighbourhood but where the processes may not be Ripley-Kelly Markov processes with respect to this neighbourhood. We show that the processes are iterated Markov processes defined by Hayat and Gubner (1996). Furthermore, we pay special attention to a subclass of interacting neighbour processes, where the density belongs to the exponential family and all neighbours of a point affect it simultaneously. A simulation study is presented to show that some simple processes of this subclass can produce clustered patterns of great variety. Finally, an empirical example is given.