Autoregressive Integrated Moving Average (ARIMA) Modeling of Time Series of Local Telephone Triage Data for Syndromic Surveillance

نویسندگان

  • Micael Widerström
  • Maria Omberg
  • Martin Ferm
  • Ann-Katrine Pettersson
  • Malin Rundvik Eriksson
  • Ingela Eckerdal
  • Johan Wiström
چکیده

1Department of Communicable Disease Control and Prevention, Jämtland County Council, Östersund, Sweden; 2Department of Clinical Microbiology, Unit of Clinical Research CenterÖstersund, Umeå University, Umeå, Sweden; 3Centre of Registers in Northern Sweden, Umeå University, Umeå, Sweden; 4Swedish Health Care Direct 1177, Jämtland County Council, Östersund, Sweden; 5Department of Clinical Microbiology, Infectious Diseases, Umeå University, Umeå, Sweden; 6Department of Communicable Disease Control and Prevention, Västerbotten County Council, Umeå, Sweden

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Comparison of autoregressive integrated moving average (ARIMA) model and adaptive neuro-fuzzy inference system (ANFIS) model

Proper models for prediction of time series data can be an advantage in making important decisions. In this study, we tried with the comparison between one of the most useful classic models of economic evaluation, auto-regressive integrated moving average model and one of the most useful artificial intelligence models, adaptive neuro-fuzzy inference system (ANFIS), investigate modeling procedur...

متن کامل

AN EXTENDED FUZZY ARTIFICIAL NEURAL NETWORKS MODEL FOR TIME SERIES FORECASTING

Improving time series forecastingaccuracy is an important yet often difficult task.Both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. In this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...

متن کامل

Time series modeling for syndromic surveillance

BACKGROUND Emergency department (ED) based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understand...

متن کامل

Which Methodology is Better for Combining Linear and Nonlinear Models for Time Series Forecasting?

Both theoretical and empirical findings have suggested that combining different models can be an effective way to improve the predictive performance of each individual model. It is especially occurred when the models in the ensemble are quite different. Hybrid techniques that decompose a time series into its linear and nonlinear components are one of the most important kinds of the hybrid model...

متن کامل

Modified Maximum Likelihood Estimation in First-Order Autoregressive Moving Average Models with some Non-Normal Residuals

When modeling time series data using autoregressive-moving average processes, it is a common practice to presume that the residuals are normally distributed. However, sometimes we encounter non-normal residuals and asymmetry of data marginal distribution. Despite widespread use of pure autoregressive processes for modeling non-normal time series, the autoregressive-moving average models have le...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 6  شماره 

صفحات  -

تاریخ انتشار 2014