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Showing 1 to 20 of 21 for “"Cumulative sum (CUSUM)"”.
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Economic Design of CUSUM Control Charts
… of a process. One such type of chart is the cumulative sum (CUSUM) chart which has advantages over other styles of control chart. A study of the economic design of CUSUM control charts is undertaken via a comparative study of long-run hourly cost (LRHC) and a computational search algorithm is …
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Monitoring for a Shift in a Process Covariance Matrix Using the Generalized Variance
… in studying the run length properties of the cumulative sum (CUSUM) U charts. Further, we will study the effect that estimating Σ₀ has on the performance of these charts. Guidance will be given for designing the Shewhart charts with runs rules with illustrative examples.
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EWMA and CUSUM control charts in the presence of correlation
In Statistical Process Control, it is usually assumed that observations taken from the process at different times are independent with a constant mean and with variation due only to measurement error. In many processes this assumption of independence is not satisfied. The lack of independence of …
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Cumulative Sum Control Charts for Censored Reliability Data
… of the data. We propose likelihood ratio based cumulative sum (CUSUM) control charts for censored lifetime data with non-normal distributions. We illustrate the development and implementation of the charts, and we evaluate their properties through simulation studies. We address the problem of …
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Investigating the relationship between non-bank financial sector development and economic growth in Namibia
… causal relationship between GDP and labour. The Cumulative Sum (CUSUM) and Cumulative Sum of Squares (CUSUMQ) test results confirmed the structural stability of the ARDL model. Policy makers are thus advised to consider promulgating laws aimed at developing the NBFI sector and those that …
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Surveillance of Poisson and Multinomial Processes
… are readily available. A multinomial cumulative sum (CUSUM) chart is proposed to monitor these types of situations. The multinomial CUSUM chart is evaluated through comparisons of performance with competing control chart methods. This research is a result of joint work with Mr. Lee J. …
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Change Point Detection in Time Series via Multivariate Singular Spectrum Analysis
… spectrum analysis (mSSA) approach with the cumulative sum (CUSUM) procedure for sequential hypothesis testing. In particular, we model the underlying dynamics of multivariate time series observations through the spatio-temporal model introduced recently in the mSSA literature. The change …
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Univariate and Multivariate Surveillance Methods for Detecting Increases in Incidence Rates
… In the first situation, the observations are assumed to be the results of independent Bernoulli trials. Some have suggested adapting the scan statistic to monitor such rates and detect a rate increase as soon as possible after it occurs. Other methods could be used in prospective surveillance, …
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Simulating Dynamical Systems from Data
… noise models, data missingness patterns, and assumptions on the factorization structure. These algorithms employ variants of the classical multivariate singular spectrum analysis (mSSA) algorithm and establish a link between time series analysis and Matrix/Tensor Completion. Second, we develop …
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Control charts applying a sequential test at fixed sampling intervals with optional sampling at fixed times
… is introduced as a generalization of the VSI cumulative sum (CUSUM) chart that uses two sampling intervals, called the universal CUSUM (UC) chart, in order to address the need for a general framework for the study of control charts that are equivalent to a sequence of SPRT’s. The UC chart can …
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Surveillance of Negative Binomial and Bernoulli Processes
… of process is given. The equivalence between two cumulative sum (CUSUM) charts, based on geometric and Bernoulli random variables is explored. An evaluation of the unit and group--runs (UGR) chart is performed, where it is shown that the in--control behavior of this chart is quite misleading and …
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Statistical Methods for Improving and Maintaining Product Reliability
… subsampling. The analysis of lifetime data assuming a completely randomized design has been well studied, but until recently analysis methodologies for more complex experimental designs with multiple error terms have not been a focus of the reliability field. This dissertation provides two …
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The Monitoring of Linear Profiles and the Inertial Properties of Control Charts
… is studied in this dissertation. It is assumed that each sample collected over time in the historical data set consists of several bivariate observations for which a simple linear regression model is appropriate, a situation common in calibration applications. Using a simulation study, the …
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Cognitive Radar Detection in Nonstationary Environments and Target Tracking
… detection, many algorithms in the literature assume a stationary environment (clutter). However, in practical scenarios, changes in the nonstationary environment can perturb the parameters of the clutter distribution or even alter the clutter distribution family, which can greatly deteriorate …
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Prospective Spatio-Temporal Surveillance Methods for the Detection of Disease Clusters
… The local Knox surveillance method uses a cumulative sum (CUSUM) control chart for monitoring the local Knox statistic, which tests for space-time clustering each time there is an incoming observation. The detection of clusters of events occurring close together both temporally and …
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Dynamic Probability Control Limits for Risk-Adjusted Bernoulli Cumulative Sum Charts
The risk-adjusted Bernoulli cumulative sum (CUSUM) chart developed by Steiner et al. (2000) is an increasingly popular tool for monitoring clinical and surgical performance. In practice, however, use of a fixed control limit for the chart leads to quite variable in-control average run length (ARL) …
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Evaluation of Scan Methods Used in the Monitoring of Public Health Surveillance Data
… weighted moving average (EWMA) charts and cumulative sum (CUSUM) charts, are examined. Two new time-to-signal measures, the average time-between-signal events and the average signal event length, are introduced to better compare the recurrence interval with the time-to-signal properties of …
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High-dimensional change point detection for mean and location parameters
… sample size $n$ and traditional distribution assumptions can easily fail. The goal is to employ non-parametric approaches to identify change points without involving intermediate estimation to cross-sectional dependence. In the first part, we consider cumulative sum (CUSUM) statistics that are …
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Exact Solution of Bayes and Minimax Change-Detection Problems
… time via epsilon-optimal parameterization of a cumulative-sum procedure. Finally, the properties of policies for change-detection problems are described and analyzed. Simple classes of formal languages are shown to be sufficient for epsilon-exact solution of change-detection problems, and …
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New progress in hot-spots detection, partial-differential-equation-based model identification and statistical computation
… detailed description of these four chapters is summarized as follows. In Chapter 1, we aim at detecting hot-spots in multivariate spatio-temporal dataset that are non-stationary over time. To realize this objective, we propose a statistical method to under the framework of tensor decomposition …
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