Forecasting fertility: An application of time series methods of parameterized model schedules - Knudsen, McNown, et al. - 1993Knudsen, C., R. McNown and A. Rogers (1993) Forecasting fertility: An application of time series methods to parameterized model schedules, Social Science Research, 22,...
GP Zhang,VL Berardi.Time series forecasting with neural network ensembles:An application for exchange rate prediction[J].Journal of the Operational Research Society,2001,6:52-66GP Zhang1and VL Berardi, "Time series forecasting with neural network ensembles: an application for exchange rate prediction...
Both day–to–day and long–term decisions often rely on some form of forecasting, where misspecification of the probability of some future value can mean misapplication of policies or misdirected business decisions. Many forecasts explicitly or implicitly assume a Gaussian confidence interval; but ...
"Grouped Functional Time Series Forecasting: An Applica- tion to Age-Specific Mortality Rates." Journal of Computational and Graphical Statistics, 26(2), 330-343. doi:10.1080/10618600.2016.1237877.Shang HL, Hyndman RJ (2017) Grouped functional time series forecasting: an appli- cation to age-...
Application of Fuzzy Rough Sets to Financial Time Series Forecasting Mariusz Podsiadlo1 and Henryk Rybinski2(B) 1 Misys Plc, London, UK mariusz.podsiadlo@misys.com 2 Warsaw University of Technology, Warsaw, Poland hrb@ii.pw.edu.pl Abstract. This paper investigates experimentally the feasibility ...
et al. Incorporating causal notions to forecasting time series: a case study. Financial Innovation, 2025, 11(1): 15. DOI:10.1186/s40854-024-00681-9 2. LI, S., BIAN, X., XU, H. Dynamic pore water pressure in asphalt mixtures under steady state vibration: Response and machine-learning...
This work proposes a novel algorithm to forecast big data time series. Based on the well-established Pattern Sequence-based Forecasting algorithm, this new approach has two major contributions to the literature. First, the improvement of the original algorithm with respect to the accuracy of predicti...
Financial time series have typical characteristics such as outliers, trends, and mean reversion. The existence of outliers will affect the effectiveness of the unknown parameter estimation in the financial time series forecasting model, so that the forecasting error of the model will be larger. Quanti...
The weekly/monthly/yearly epidemic data form a time series of counts. Analyzing and forecasting time series of counts remain a useful technique of getting information needed for successful policy making and management of epidemics. Before modeling a count time series, an analyst should be familiar ...
Forecasting is also an area which has witnessed a paradigm shift in its approach. In this work, we have used the time series of the index values of the Auto sector in India during January 2010 to December 2015 for a deeper understanding of the behavior of its three constituent components, ...