Multivariate control charts based on Bayesian state space models

This paper develops a new multivariate control charting method for vector autocorrelated and serially correlated processes. The main idea is to propose a Bayesian multivariate local level model, which is a generalization of the Shewhart-Deming model for autocorrelated processes, in order to provide the predictive error distribution of the process and then to apply a univariate modified EWMA control chart to the logarithm of the Bayes' factors of the predictive error density versus the target error density. The resulting chart is proposed as capable to deal with both the non-normality and the autocorrelation structure of the log Bayes' factors. The new control charting scheme is general in application and it has the advantage to control simultaneously not only the process mean vector and the dispersion covariance matrix, but also the entire target distribution of the process. Two examples of London metal exchange data and of production time series data illustrate the capabilities of the new control chart.Comment: 19 pages, 6 figure

Robustness of DEWMA versus EWMA Control Charts to Non-Normal Processes

Exponentially weighted moving average (EWMA) and double EWMA (DEWMA) control charts were designed under the normality assumption. This study considers various skewed (Gamma) and symmetric non-normal (t) distributions to examine the effect of non-normality on the average run length (ARL) performance of EWMA and DEWMA. ARL performances were investigated and compared using Monte Carlo simulations. Results show that DEWMA charts can be designed to be robust to non-normality, that the ARL performances of EWMA and DEWMA charts were more robust to t distributions and DEWMA was more robust to non-normality for larger values of the smoothing parameter

Discussion paper. Conditional growth charts

Growth charts are often more informative when they are customized per subject, taking into account prior measurements and possibly other covariates of the subject. We study a global semiparametric quantile regression model that has the ability to estimate conditional quantiles without the usual distributional assumptions. The model can be estimated from longitudinal reference data with irregular measurement times and with some level of robustness against outliers, and it is also flexible for including covariate information. We propose a rank score test for large sample inference on covariates, and develop a new model assessment tool for longitudinal growth data. Our research indicates that the global model has the potential to be a very useful tool in conditional growth chart analysis.Comment: This paper discussed in: [math/0702636], [math/0702640], [math/0702641], [math/0702642]. Rejoinder in [math.ST/0702643]. Published at http://dx.doi.org/10.1214/009053606000000623 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Demographics and financial asset prices in the major industrial economies

This paper explores the relationship between demographics and aggregate financial asset prices in 7 OECD countries over the past 50 years. Unlike most extant work it adopts an international as well as US focus, and also includes non-demographic variables usually considered to influence asset prices in the econometric specification. Furthermore, we examine effects on bond yields as well as share prices. The results indicate a significant link between panel, international and US demographics on the one hand, and real stock prices and real bond yields on the other. The international results are of particular interest given their robustness and the logic of international financial integration. Generally, an increase in the fraction of middle-aged people (aged 40-64) tends to boost real asset prices. A corollary is that a decline in this cohort in coming decades will tend to weaken them. More tentative results including estimated effects of the over-65 cohort in the US suggest a more severe downturn is possible, thus underlining the potential market risks associated with sole reliance on fully funded pension schemes