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Optimal exponentially weighted moving average (EWMA) plans for detecting seasonal epidemics when faced with non-homogeneous negative binomial counts
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Optimal exponentially weighted moving average (EWMA) plans for detecting seasonal epidemics when faced with non-homogeneous negative binomial counts (2011)Optimal exponentially weighted moving ave…Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology (2008)Bayesian Disease Mapping: Hie…Adaptive Thresholds (2006)Adaptive ThresholdsA Markov Chain Model for the Adaptive CUSUM Control Chart (2006)A Markov Chain Model for the …An Adaptive Exponentially Weighted Moving Average Control Chart (2003)An Adaptive Exponentially Wei…CUSUM Charts for Signalling Varying Location Shifts (2000)CUSUM Charts for Signalling V…An approximate CUSUM procedure for surveillance of health events (1999)An approximate CUSUM procedur…Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements (1990)Exponentially Weighted Moving…Changepoint detection in non-exchangeable data (2022)Changepoint detection in non-…Monitoring of three-phase variations in the mortality of COVID-19 pandemic using control charts: where does Pakistan stand? (2021)Monitoring of three-phase var…Quality Control - Intelligent Manufacturing, Robust Design and Charts (2020)Quality Control - Intelligent…Monitoring events with application to syndromic surveillance using social media data (2020)Monitoring events with applic…Real-time monitoring of events applied to syndromic surveillance (2019)Real-time monitoring of event…Effect of neglecting autocorrelation in regression EWMA charts for monitoring count time series (2018)Effect of neglecting autocorr…The use of length-biased distributions in statistical monitoring (2017)The use of length-biased dist…CUSUM chart to monitor autocorrelated counts using Negative Binomial GARMA model (2017)CUSUM chart to monitor autoco…Surveillance of Nonhomogeneous Poisson Processes (2014)Surveillance of Nonhomogeneou…The Negative Binomial Exponentially Weighted Moving Average Chart with Estimated Control Limits (2013)The Negative Binomial Exponen…CONTINUOUS INSPECTION SCHEMES (1954)Introduction to Statistical Quality Control (1992)Adaptive CUSUM control chart with variable sampling intervals (2009)The computation of average run length and average time to signal: an overview (2013)Univariate Dynamic Screening System: An Approach For Identifying Individuals With Irregular Longitudinal Behavior (2013)Cumulative Sum Charts and Charting for Quality Improvement (1998)The Use of Control Charts in Health-Care and Public-Health Surveillance (2006)A statistical approach to social network monitoring (2016)Statistical process control charts for monitoring military injuries (2017)Optimal Properties of Exponentially Weighted Forecasts (1960)A Multivariate Exponentially Weighted Moving Average Control Chart (1992)A review of multivariate control charts (1995)Research Issues and Ideas in Statistical Process Control (1999)Sampling Inspection of Continuous Processes with No Autocorrelation Between Successive Results (1960)A Comparison of Some Control Chart Procedures (1966)Statistical Issues in the Prospective Monitoring of Health Outcomes Across Multiple Units (2004)Count data regression charts for the monitoring of surveillance time series (2008)Likelihood-Based EWMA Charts for Monitoring Poisson Count Data With Time-Varying Sample Sizes (2012)A Simple Method for Studying Run – Length Distributions of Exponentially Weighted Moving Average Charts (1987)SPCQCharts for Start-Up Processes and Short or Long Runs (1991)Improving EWMA Plans for Detecting Unusual Increases in Poisson Counts (2009)A cusum change-point detection algorithm for non-stationary sequences with application to data network surveillance (2010)Effective Control Charts for Monitoring the NGINAR(1) Process (2015)An Overview of Control Charts for High‐quality Processes (2016)Monitoring processes with multiple dependent production lines using time between events control charts (2023)Simultaneous monitoring of multivariate time between events and their magnitude using multivariate marked Hawkes point process (2023)Portfolio Selection: Efficient Diversification of Investments. 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References

  • 1990Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements1,939 cited
  • 2008Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology436 cited
  • 2003An Adaptive Exponentially Weighted Moving Average Control Chart375 cited
  • 2000CUSUM Charts for Signalling Varying Location Shifts258 cited
  • 1999An approximate CUSUM procedure for surveillance of health events120 cited
  • 2006A Markov Chain Model for the Adaptive CUSUM Control Chart112 cited
  • 2006Adaptive Thresholds55 cited

Cited by

  • 2014Surveillance of Nonhomogeneous Poisson Processes26 cited
  • 2019Real-time monitoring of events applied to syndromic surveillance22 cited
  • 2020Quality Control - Intelligent Manufacturing, Robust Design and Charts16 cited
  • 2021Monitoring of three-phase variations in the mortality of COVID-19 pandemic using control charts: where does Pakistan stand?16 cited
  • 2017CUSUM chart to monitor autocorrelated counts using Negative Binomial GARMA model15 cited
  • 2022Changepoint detection in non-exchangeable data10 cited
  • 2017The use of length-biased distributions in statistical monitoring10 cited
  • 2020Monitoring events with application to syndromic surveillance using social media data

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8 cited
  • 2018Effect of neglecting autocorrelation in regression EWMA charts for monitoring count time series8 cited
  • 2013The Negative Binomial Exponentially Weighted Moving Average Chart with Estimated Control Limits7 cited