Conveners
Process 1
- Chair: András Zempléni (Eötvös Loránd University, Budapest)
For the last twenty years, a plethora of new ``memory-type'' control charts have been proposed. They share some common features: (i) deceptively good zero-state average run-length (ARL) performance, but poor steady-state performance, (ii) design, deployment and analysis significantly more complicated than for established charts, (iii) comparisons made to unnecessarily weak competitors, and...
In this work, we develop and study upper and lower one-sided CUSUM control charts for monitoring correlated counts with finite range. Often in practice, data of that kind can be adequately described by a first-order binomial integer-valued ARCH model (or BINARCH(1)). The proposed charts are based on the likelihood ratio and can be used for detecting upward or downward shifts in process mean...
In Statistical Process Control/Monitoring (SPC/M) our interest is in detecting when a process deteriorates from its “in control” state, typically established after a long phase I exercise. Detecting shifts in short horizon data of a process with unknown parameters, (i.e. without a phase I calibration) is quite challenging.
In this work, we propose a self-starting Bayesian change point...