Directed monitoring using Cuscore charts for seasonal time series

Autocorrelated Process Monitoring Using Triggered Cuscore Charts

Some of the most widely-investigated control charting techniques for autocorrelated data are based on time series residuals. If the mean shift in the autocorrelated process is a sudden step shift, the resulting mean shift in the residuals is time varying and has been referred to as the fault signature. Traditional residual based charts, such as a Shewhart, CUSUM, or EWMA on the residuals, do no...

Specific Signal Detection Charts Using Generalized Likelihood Ratios

Simulations are done to compare the performances of Generalized Likelihood Ratio (GLR) and Cuscore charts for detecting specific signals hidden in noise. Two different types of signals are considered: a sine wave and a linear trend. Two different cases are analyzed, a known signal form and parameter and a known signal form but unknown signal parameter. Both the initial performances and steady-s...

Poisson regression charts for the monitoring of surveillance time series

This paper presents a Poisson control chart for monitoring time series of counts typically arising in the surveillance of infectious diseases. The in-control mean is assumed to be time-varying and linear on the log-scale with intercept and seasonal components. If a shift in the intercept occurs the system goes out-of-control. Novel is that the magnitude of the shift does not have to be specifie...

Comparison of the Cuscore, Glrt and Cusum Control Charts for Detecting a Dynamic Mean Change

بکارگیری نمودارهای کنترل در پایش عملکرد مراقبت های اولیه ی بهداشتی

Background and Aim: Monitoring and evaluation are basic components of any health program. Control charts show clearly the process performance trend longitudinally and help managers and staff to detect general and specific variations and evaluate the process performance correctly. This study was conducted to design and utilize control charts in the primary health care (PHC) system. Materials an...