Optimal CUSUM and adaptive CUSUM charts with auxiliary information for process mean

The CUSUM chart is good enough to detect small-to-moderate shifts in the process parameter(s) as it can be optimally designed to detect a particular shift size. The adaptive CUSUM (ACUSUM) chart provides good detection over a range of shift sizes because of its ability to update the reference parameter using the estimated process shift. In this paper, we propose auxiliary-information-based (AIB) optimal CUSUM (OCUSUM) and ACUSUM charts, named AIB-OCUSUM and AIB-ACUSUM charts, using a difference estimator of the process mean. The performance comparisons between existing and proposed charts are made in terms of the average run length (ARL), extra quadratic loss and integral relative ARL measures. It is found that the AIB-OCUSUM and AIB-ACUSUM charts are more sensitive than the AIB-CUSUM and ACUSUM charts, respectively. Moreover, the AIB-ACUSUM chart surpasses the AIB-OCUSUM chart when detecting a range of mean shift sizes. Illustrative examples are given to support the theory.     

An exponentially weighted moving average chart controlling false discovery rate

A new control chart is developed by using the exponentially weighted moving average (EWMA) statistics and a multiple testing procedure for controlling false discovery rate. The multiple testing procedure considers not only the current EWMA statistic, but also a given number of previous statistics at the same time. Numerical simulations are accomplished to evaluate the performance of the proposed control chart in terms of the average run length and the conditional expected delay. The results are compared with those of the existing control charts including the X-bar chart, EWMA, and cumulative sum control charts. Case studies with real data-sets are also presented.     

Cusum quality control-multivariate approach

A new multivariate approach to quality control is presented. On the basis of sequential probability ratio tests, a multivariate cumulative sum chart is derived. Using an approximation to the noncentral x² distribution, a linear decision rule is obtained.     

Performance comparison of some likelihood ratio-based statistical surveillance methods

Using Markov chain representations, we evaluate and compare the performance of cumulative sum (CUSUM) and Shiryayev–Roberts methods in terms of the zero- and steady-state average run length and worst-case signal resistance measures. We also calculate the signal resistance values from the worst- to the best-case scenarios for both the methods. Our results support the recommendation that Shewhart limits be used with CUSUM and Shiryayev–Roberts methods, especially for low values of the size of the shift in the process mean for which the methods are designed to detect optimally.     

Robust dual-CUSUM control charts for contaminated processes

ABSTRACT

In this article, we improve the efficiency of the Dual CUSUM chart (which combines the designs of two CUSUM structures to detect a range of shift) by focusing on its robustness, ability to resist some disturbances in the process environment and violation of basic assumptions. We do that, by proposing some robust estimators for constructing the chart for both contaminated and uncontaminated environments. The average run length is used as the performance evaluation measure of the charts. After comparing the performances of the proposed charts based on the estimators, it is noticed that the tri-mean estimator out-performs others in all ramifications. Next to it in performance is the Hodges-Lehmann and midrange estimators. We substantiated the simulation results of the study by applying the scheme on a real-life data set.     

多抽样率频率抽样FIR数字滤波器设计

采用多抽样率方法设计频率抽样FIR数字滤波器,可以获得性能优异的滤波器,以消除心电信号ECG中的基线漂移和工频干扰,对目前类似滤波器存在的截止频率不易控制、通带和阻带纹波过大、工频阻带过窄、易受工频波动干扰或消除基线漂移时对ECG的低频部分削得过多等问题,提出了一个较好的解决办法。相对于IIR滤波器或模拟滤波器避免了因非线性相位滤波带来的失真问题。     

Signaling NBER turning points: a sequential approach

The dates of the U.S. business cycle are reported by the National Bureau of Economic Research with a considerable delay, so an early notion of turning points is of particular interest. This paper proposes a novel sequential classification approach designed for timely signaling these turning points, using the time series of coincident economic indicators. The approach exhibits a range of theoretical optimality properties for early signaling, moreover, it is transparent and easy to implement. The empirical study evaluates the signaling ability of the proposed methodology.     

Double-sampling control charts for attributes

In this article, we propose a double-sampling (DS) np control chart. We assume that the time interval between samples is fixed. The choice of the design parameters of the proposed chart and also comparisons between charts are based on statistical properties, such as the average number of samples until a signal. The optimal design parameters of the proposed control chart are obtained. During the optimization procedure, constraints are imposed on the in-control average sample size and on the in-control average run length. In this way, required statistical properties can be assured. Varying some input parameters, the proposed DS np chart is compared with the single-sampling np chart, variable sample size np chart, CUSUM np and EWMA np charts. The comparisons are carried out considering the optimal design for each chart. For the ranges of parameters considered, the DS scheme is the fastest one for the detection of increases of 100% or more in the fraction non-conforming and, moreover, the DS np chart is easy to operate.