techniques to model the properties of a global mean temperature dataset in order to develop a parsimonious forecasting model for … non-seasonal unit root testing with and without structural breaks, as well as ARIMA and GARCH modelling. A forecasting …

.Behavioral modeling is a computationally challenging problem--real world data sets can contain on the order of 10^30,000 possible … behaviors in any given situation. This work presents several scalable frameworks for modeling and forecasting agent behavior …, particularly in the realm of international security dynamics. A probabilistic logic formalism for modeling and forecasting behavior …

This paper provides a significant numerical evidence for out-of-sample forecasting ability of linear Gaussian interest …

This study utilizes common time series forecasting methods to determine which of several simple, popular time series … forecasting techniques was the best predictor of the decline in United States weekly RevPAR as the lodging industry entered its … RevPAR data and utilized that data to test various moving average, exponential, and seasonal forecasting methods. The study …