Methods for on-line monitoring of business cycles are compared with respect to the ability of early prediction of the next tum by an alarm for a tum in a leading index. Three likelihood-based methods for turning point ...

Methods for on-line monitoring of business cycles are compared with respect to the ability of early prediction of the next turn by an alarm for a turn in a leading index. Three likelihood based methods for turning point ...

When making political decisions, the ability to make correct predictions about the behaviour of the business cycle in the future is important. The ability to forecast business cycles determines the success of, for example, ...

Varningssystem behövs t.ex. vid intensivövervakning, smittskydd, miljörisker och kvalitetskontroll av vården. Statistiska varningssystem signalerar när det skett en väsentlig ändring och man vet vilka egenskaper systemet ...

Seasonal adjustment is important in for example economic time series where the variation can be due to both seasonal and cyclical movements. In a situation where we want to detect a turning point of a cyclical process ...

Multivariate surveillance is of interest in many areas such as industrial production, bioterrorism detection, spatial surveillance, and financial transaction strategies. Some of the suggested approaches to multivariate ...

A statistical surveillance system gives a signal as soon as data give enough evidence of an important event. We consider on-line surveillance systems for detecting changes in influenza incidence. One important feature of ...

The detection of a change from a constant level to a monotonically increasing (or decreasing) regression is of special interest for the detection of outbreaks of, for example, epidemics. A maximum likelihood ratio statistic ...

In this report a method for monitoring time series with cycles is presented. It is a nonparametric approach for detecting the turning point of the cycles. Time series of business indicators often exhibit cycles that can ...

A regression may be constant for small values of the independent variable (for example time), but then a monotonic increase starts. Such an “outbreak” regression is of interest for example in the study of the outbreak of ...