Conveners
INVITED ISBIS
- Daniel R. Jeske (University of California, Riverside)
In statistical evaluation of process effectiveness using statistics like capability or performance indices there are strong assumptions such as normality, homogeneity or independence. It can be problematic to check the assumptions for automated unsupervised data streams. Approaches are applied to standard data as well as data violating assumptions, like probability models. It has been shown...
Interval-valued data are often encountered in practice, namely when only upper and lower bounds on observations are available. As a simple example, consider a random sample $x_1, \dots, x_n$ from a distribution $\Phi$; the task is to estimate some of the characteristics of $\Phi$, such as moments or quantiles. Assume that the data $x_1, \dots, x_n$ are not observable; we have only bounds...
The most widely used methods for online change detection have been developed within the Statistical Process Control framework. These methods are typically used for controlling the quality during a manufacturing process. In general, the problem concerns detecting whether or not a change has occurred and identifying the times of any such changes. In the last decade, some new approaches based on...