论文信息 - CUSUM and EWMA Control Charts for Negative Binomial Distribution

CUSUM and EWMA Control Charts for Negative Binomial Distribution

In public health surveillance, control charts based on the daily number of hospitalizations may be monitored to detect outbreaks and/or to plan the offer of health assistance. A generalized linear model with negative binomial distribution is proposed to the number of hospitalizations, and it depends on the exposed population and covariates, as the day of week and sines and cosines to describe the seasonality. The objective of this study is to compare (in terms of ARL1) the exponentially weighted moving average and the cumulative sum control charts for monitoring daily counts based on simulations of the daily number of hospitalizations due to respiratory diseases for people over 65 years old in Sao Paulo city (Brazil). Copyright © 2016 John Wiley & Sons, Ltd.

[1] Douglas C. Montgomery,et al. Some Current Directions in the Theory and Application of Statistical Process Monitoring , 2014 .

[2] Michael Höhle,et al. Count data regression charts for the monitoring of surveillance time series , 2008, Comput. Stat. Data Anal..

[3] Guan Yu,et al. Variance stabilizing transformations of Poisson, binomial and negative binomial distributions , 2009 .

[4] William N. Venables,et al. Modern Applied Statistics with S , 2010 .

[5] Paul H. Garthwaite,et al. Statistical methods for the prospective detection of infectious disease outbreaks: a review , 2012 .

[6] William H. Woodall,et al. The Use of Control Charts in Health-Care and Public-Health Surveillance , 2006 .

[7] C. Gourieroux,et al. Pseudo Maximum Likelihood Methods: Applications to Poisson Models , 1984 .

[8] G. Rossi,et al. An approximate CUSUM procedure for surveillance of health events. , 1999, Statistics in medicine.

[9] Airlane Pereira Alencar,et al. CUSUM control charts to monitor series of Negative Binomial count data , 2017, Statistical methods in medical research.

[10] A. W. Kemp,et al. Univariate Discrete Distributions: Johnson/Univariate Discrete Distributions , 2005 .