We consider the minimax quickest detection problem of an unobservable time of change in the rate of an inhomogeneous Poisson process. We seek a stopping rule that minimizes the robust Lorden criterion, formulated in terms of the number of events until detection, both for the worst-case delay and the false alarm constraint. In the Wiener case, such a problem has been solved using the so-called c...

BACKGROUND The laparoscopic approach for colorectal pathologies is becoming more widely used, and surgeons have had to learn how to perform this new technique. The purpose of this work is to study the indicators of the learning curve for laparoscopic colectomy in a community hospital and to find when the group begins to improve. METHODOLOGY From January 1 2005 to December 31 2012, 313 consecu...

OBJECTIVE To assess clinical measurement competency by two sequential test formulations [resetting sequential probability ratio test (R-SPRT) and learning curve cumulative summation (LC-CUSUM)]. DESIGN Numerical simulation and retrospective observational study. SETTING Obstetric ultrasound department. PARTICIPANTS Cohorts of 10,000 simulated trainees and 62 obstetric sonographers training...

The focus of this paper is on stochastic change detection applied in connection with active fault diagnosis (AFD). An auxiliary input signal is applied in AFD. This signal injection in the system will in general allow us to obtain a fast change detection/isolation by considering the output or an error output from the system. The classical cumulative sum (CUSUM) test will be modified with respec...

Most control charts for variables data are constructed upon the assumption that the observations from a process are independent. In most applications however this assumption does not hold. The performance of process control schemes have to be evaluated in such circumstances. However most of the work published deal with shifts in the location of correlated processes. In this paper, the ARL perfo...

Monitoring inhomogeneous Poisson processes with varying sample sizes has attracted considerable attention recently in both industrial quality control and public health surveillance. One of the key challenges in these applications is that a change in incidence rate may be masked by changes of sample sizes. The conventional Poisson cumulative sum (CUSUM) chart designed for detecting a pre-specifi...

Statistical process control (SPC) requires statistical methodologies that detect changes in the pattern of data over time. The common methodologies, such as Shewhart, cumulative sum (cusum), and exponentially weighted moving average (EWMA) charting, require the in-control values of the process parameters, but these are rarely known accurately. Using estimated parameters, the run length behavior...

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...

This paper investigates control charts for detecting special causes in an ARIMA(0,1,1) process that is being adjusted automatically after each observation using a minimum mean-squared error adjustment policy. It is assumed that the adjustment mechanism is designed to compensate for the inherent variation due to the ARIMA(0,1,1) process, but it is desirable to detect and eliminate special causes...

Risk-adjusted CUSUM schemes are designed to monitor the number of adverse outcomes following a medical procedure. An approximation of the average run length (ARL), which is the usual performance measure for a risk-adjusted CUSUM, may be found using its Markov property. We compare two methods of computing transition probability matrices where the risk model classifies patient populations into di...