Time series models

Time series models

Systems that examine series of historical data; sometimes used as a means of technical forecasting, by examining moving averages.
References in periodicals archive ?
Forecasting, Structural Time Series Models and The Kalman Filter.
Time series models have been developed to decompose the trend, seasonal, and cyclical component of the series.
Among the topics are the design and analysis of 2k-p x 2q-r split plot experiments, quality quandaries: forecasting with seasonal time series models, the scientific context of quality improvement, a 20-year retrospective of Quality Engineering, and reducing start time delays in operating rooms.
Data generating process (DGP) for RTC from 2007 to 2014, for monthly number of fatal and injured victims were analyzed using autoregressive integrated moving average and vector auto regression, time series models.
Researchers used two time series models, ARIMA and ESM (exponential smoothing method).
univariate) time series models and econometric (or causal) models.
Time series models are applied on the historical and transactional EDR data to improve the future EDR predictions for a given geographical location.
Traffic prediction is of great significance in network management [1], and it is usually performed through time series models [2].
For count data, so far there are two main classes of time series models that have been developed in recent years: state-space models and thinning models.
Three types of models are often used to generate estimates of the fiscal multiplier--macroeconometric forecasting models, time series models, and dynamic stochastic general equilibrium (DSGE) models.
Moreover, as there have been many different time series models for prediction, it will be of genuine interest to evaluate the best suitability of a model for the prediction of epidemic incidence.
The text includes 10 chapters, most of which are devoted at least in part to discussions about regression or time series models, the bread-and-butter tools for most economists.