Empirical Non-Parametric Control Charts: Estimation Effects and Corrections

Owing to the extreme quantiles involved, standard control charts are very sensitive to the effects of parameter estimation and non-normality. More general parametric charts have been devised to deal with the latter complication and corrections have been derived to compensate for the estimation step, both under normal and parametric models. The resulting procedures offer a satisfactory solution over a broad range of underlying distributions. However, situations do occur where even such a large model is inadequate and nothing remains but to consider non- parametric charts. In principle, these form ideal solutions, but the problem is that huge sample sizes are required for the estimation step. Otherwise the resulting stochastic error is so large that the chart is very unstable, a disadvantage that seems to outweigh the advantage of avoiding the model error from the parametric case. Here we analyse under what conditions non-parametric charts actually become feasible alternatives for their parametric counterparts. In particular, corrected versions are suggested for which a possible change point is reached at sample sizes that are markedly less huge (but still larger than the customary range). These corrections serve to control the behaviour during in-control (markedly wrong outcomes of the estimates only occur sufficiently rarely). The price for this protection will clearly be some loss of detection power during out-of-control. A change point comes in view as soon as this loss can be made sufficiently small.     

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.     

American High School Students’ Perceptions of Determinants of Life Satisfaction

Life satisfaction can be assessed either globally or with regard to satisfaction with specific domains of life. The latter multidimensional approach presumes science has delineated with confidence the specific domains most relevant to evaluating whether the criteria for a good life have been met. This paper shares results of a qualitative study of the perceived determinants of life satisfaction among 30 high school students who were diverse in terms of mental health; 6–10 participants were classified as complete mental health, vulnerable, symptomatic but content, or troubled at two time points separated by a year. Thematic analyses of transcribed individual interviews suggested eight themes that capture the domains of life adolescents perceive influence their happiness. These themes are compared and contrasted to domains included in existing multi-dimensional measures of youth life satisfaction. The factors likely to be particularly salient to students with different levels of mental health are noted.

     

High technology organizations: Context, organization and people

Firms in global high technology industries face key challenges. This paper presents an integrative framework that delineates aspects of their context, organization and human resources. It also identifies tensions within the firm that can only be resolved by increasing the capacity of the firm to deal with multiple and conflicting pressures. High technology firms muct be adept at resolving tensions and learning in a very fast paced and changing world.     

Suicide ideation among a stratified sample of rural and urban adolescents

This study examined factors associated with sucidal ideation among a stratified sample of rural and urban adolescents. Data was collected on 1,728 eighth and tenth grade southern Nevada students from 23 schools. No overall differences were found between rural and urban adolescents, although results did indicate that grade, gender, and school achievement variations exist between rural and urban student populations. Implications for social workers and other youth service providers are discussed.     

Suicide ideation,attempts and abuse among incarcerated gang and nongang delinquents

The present study examines suicide ideation and attempts as well as reported levels of physical and sexual abuse among gang and nongang-involved incarcerated youth. The self-report survey data were collected from 334 males and 61 females who were incarcerated in Nevada youth correctional facilities in the summer of 1994. Over half (58.3 percent) of the males and nearly half (45.2 percent) of the females reported being gang members. Surprisingly high rates of abuse (more than 70 percent for both physical and sexual abuse) were found among the incarcerated females of this study. Females reported significantly more suicide attempts and were more likely to have been physically and sexually abused than males. Nongang males reported significantly more suicide attempts and were more likely to report sexual abuse than gang-involved males. Among the gang-involved delinquents, females reported significantly more suicide attempts than males. In addition, gang members who reported sexual abuse were more likely to have higher levels of suicide ideationand to have attempted suicide. Implications for youth correction specialists and social workers are discussed.The data for this study were collected under Grant #000616 from the Nevada Agricultural Experiment Station.     

Forecasting Multivariate Road Traffic Flows Using Bayesian Dynamic Graphical Models,Splines and Other Traffic Variables

Traffic flow data are routinely collected for many networks worldwide. These invariably large data sets can be used as part of a traffic management system, for which good traffic flow forecasting models are crucial. The linear multiregression dynamic model (LMDM) has been shown to be promising for forecasting flows, accommodating multivariate flow time series, while being a computationally simple model to use. While statistical flow forecasting models usually base their forecasts on flow data alone, data for other traffic variables are also routinely collected. This paper shows how cubic splines can be used to incorporate extra variables into the LMDM in order to enhance flow forecasts. Cubic splines are also introduced into the LMDM to parsimoniously accommodate the daily cycle exhibited by traffic flows. The proposed methodology allows the LMDM to provide more accurate forecasts when forecasting flows in a real high‐dimensional traffic data set. The resulting extended LMDM can deal with some important traffic modelling issues not usually considered in flow forecasting models. Additionally, the model can be implemented in a real‐time environment, a crucial requirement for traffic management systems designed to support decisions and actions to alleviate congestion and keep traffic flowing.     

Exceedance probabilities for parametric control charts

Common control charts assume normality and known parameters. Quite often, these assumptions are not valid and large relative errors result in the usual performance characteristics such as the false alarm rate or the average run length. A fully nonparametric approach can form an attractive alternative but requires more Phase I observations than usually available. Sufficiently general parametric families then provide realistic intermediate models. In this article, the performance of charts based on such families is considered. Exceedance probabilities of the resulting stochastic performance characteristics during in-control are studied. Corrections are derived to ensure that such probabilities stay within prescribed bounds. Attention is also devoted to the impact of the corrections for an out-of-control process. Simulations are presented both to illustrate and to demonstrate that the approximations obtained are sufficiently accurate for practical usage.     

Empirical nonparametric control charts for high-quality processes

For attribute data with (very) small failure rates often control charts are used which decide whether to stop or to continue each time r failures have occurred, for some r?1. Because of the small probabilities involved, such charts are very sensitive to estimation effects. This is true in particular if the underlying failure rate varies and hence the distributions involved are not geometric. Such a situation calls for a nonparametric approach, but this may require far more Phase I observations than are typically available in practice. In the present paper it is shown how this obstacle can be effectively overcome by looking not at the sum but rather at the maximum of each group of size r.