Recent advances in mathematical modeling and inference methodologies have enabled development of systems capable of forecasting seasonal influenza epidemics in temperate regions in real-time. However, in subtropical and tropical regions, influenza epidemics can occur throughout the year, making routine forecast of influenza more challenging. Here we develop and report forecast systems that are ...

Forecast combination has been proven to be a very important technique to obtain accurate predictions for various applications in economics, finance, marketing and many other areas. In many applications, forecast errors exhibit heavy-tailed behaviors for various reasons. Unfortunately, to our knowledge, little has been done to obtain reliable forecast combinations for such situations. The famili...

There has been a dramatic increase over the past decade in the number of firms that source finished product from overseas. While this has reduced procurement costs, it has increased supply risk; procurement lead times are longer and are often unreliable. In deciding when and how much to order, firms must consider the lead time risk and the demand risk, i.e., the accuracy of their demand forecas...

We present a forecast-based adaptive management framework for water supply reservoirs and evaluate the contribution of long-term inflow forecasts to reservoir operations. Our framework is developed for snow-dominated river basins that demonstrate large gaps in forecast skill between seasonal and inter-annual time horizons. We quantify and bound the contribution of seasonal and inter-annual fore...

A number of previous studies have shown that a combination of forecasts typically outperforms any component forecast. Service managers may wish to use forecast combination to improve forecast accuracy in predicting retail sales. In this study, revenue data from an actual service company is used to generate and test a least absolute value (LAV) regression model for forecast combination. The LAV ...

This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP). The assimilation scheme, System for Ocean Forecast and Analysis (SOFA), is a reduced order Optimal Interpolation (OI) scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF). The d...

The Southeast Alaska Coastal Monitoring (SECM) project has been sampling juvenile salmon (Oncorhynchus spp.) and associated environmental parameters in northern Southeast Alaska (SEAK) annually since 1997 to better understand effects of environmental change on salmon production. A pragmatic application of the annual sampling effort is to forecast the abundance of adult salmon returns in subsequ...

Prior literature observes that information uncertainty exacerbates investor underreaction behavior. In this paper, I investigate whether, as professional investment intermediaries, sellside analysts suffer more behavioral biases in cases of greater information uncertainty. I show that greater information uncertainty predicts more positive (negative) forecast errors and subsequent forecast revis...

In the framework of TEI@I methodology, this paper proposes a combined forecast method integrating contextual knowledge (CFMIK). With the help of contextual knowledge, this method considers the effects of those factors that cannot be explicitly included in the forecast model, and thus it can efficiently decrease the forecast error resulted from the irregular events. Through a container throughpu...