CUSUM control schemes for Gaussian processes

A CUSUM control scheme for detecting a change point in a Gaussian process is derived. An upper and a lower bound for the distribution of the run length and for its moments is given. In a Monte Carlo study the average run length (ARL) of this chart is compared with the ARL of two other CUSUM procedures which are based on approximations to the sequential probability ratio, and, moreover, with EWMA schemes for autocorrelated data. Results on the optimal choice of the reference value are presented. Furthermore it is investigated how these charts behave if the model parameters are estimated.     

Spatial robust small area estimation

The accuracy of recent applications in small area statistics in many cases highly depends on the assumed properties of the underlying models and the availability of micro information. In finite population sampling, small sample sizes may increase the sensitivity of the modeling with respect to single units. In these cases, area-specific sample sizes tend to be small such that normal assumptions, even of area means, seem to be violated. Hence, applying robust estimation methods is expected to yield more reliable results. In general, two robust small area methods are applied, the robust EBLUP and the M-quantile method. Additionally, the use of adequate auxiliary information may further increase the accuracy of the estimates. In prediction based approaches where information is needed on universe level, in general, only few variables are available which can be used for modeling. In addition to variables from the dataset, in many cases further information may be available, e.g. geographical information which could indicate spatial dependencies between neighboring areas. This spatial information can be included in the modeling using spatially correlated area effects. Within the paper the classical robust EBLUP is extended to cover spatial area effects via a simultaneous autoregressive model. The performance of the different estimators are compared in a model-based simulation study.     

Recall of Nonverbal Cues: Exploring a New Definition of Interpersonal Sensitivity

Interpersonal sensitivity, defined as the accurate recall of another person’s nonverbal behavior, was measured in two studies. In Study 1, nonverbal recall accuracy (NRA) was based on recall of cues expressed by a man and/or woman being interviewed on videotape. Retest reliability after 2 weeks was satisfactory and the male and female tests demonstrated sufficient convergence. Participants could assess their own recall accuracy at better than chance levels; ability to decode the meanings of visual nonverbal cues was positively related to NRA; discriminant validity of NRA was demonstrated with regard to general cognitive ability; and women had higher NRA than men. In Study 2, NRA was based on recall of a live interaction partner. Women again had higher NRA than men; NRA was significantly better than chance; and higher NRA was associated with more smiling and self-reported positive affect during the interaction. Nonverbal recall accuracy is a promising new definition of interpersonal sensitivity.

Distribution function and percentage points for the central and noncentral F-distribution

Programs in Standard-Fortran for the computation of the distribution function and percentage points of the central and noncentral F-distribution are given.     

Israel's long-term care insurance law after a decade of implementation

Israel's Long-Term Care Insurance (LTCI) law has been in effect for a decade. It is timely to review the effects of this legislation with a view to identifying possible directions for reform and lessons for other countries considering the introduction of a similar social insurance scheme. The paper considers the law's effects in terms of the size and characteristics of the beneficiary population, the coverage of the scheme, its financial standing, the rate of institutionalization of the elderly, the caregiving burden, the service delivery system, and the overall scope of long-term care services for the aged. Israel's experience has lessons for financing arrangements, target efficiency, service delivery arrangements, and the construction of the burden of care.     

Broadening the Scope of Benchmarking: Radar Charts and Employment Systems

Over the last few years, ‘benchmarking’ advanced to a key word in organizational development and change management. Originally a tool in business studies to search for best practice that led to superior performance, increasingly benchmarking also became practice in non-profit and public institutions. Notably, the European Commission uses benchmarking as an instrument to monitor its employment guidelines. The radar chart approach is one of a number of special analytical tools that has been developed in this connection. The paper discusses the advantages and limits of benchmarking labour market performance by radar charts, recommends a broadening of the scope by using the employment systems approach and provides, in both cases, examples of application.     

Correction to: Comparison of joint control schemes for multivariate normal i.i.d. output

AStA Advances in Statistical Analysis - In the original paper, we incorrectly stated that...     

CUSUM control schemes for monitoring the covariance matrix of multivariate time series

Modified cumulative sum (CUSUM) control charts and CUSUM schemes for residuals are suggested to detect changes in the covariance matrix of multivariate time series. Several properties of these schemes are derived when the in-control process is a stationary Gaussian process. A Monte Carlo study reveals that the proposed approaches show similar or even better performance than the schemes based on the multivariate exponentially weighted moving average (MEWMA) recursion. We illustrate how the control procedures can be applied to monitor the covariance structure of developed stock market indices.