One important problem in the marketing and user growth for businesses is to infer the marginal gains of specific campaigns or strategies, which is crucial for the decision makers to determine whether to carry on or terminate certain policies. However, in most cases the return of gaining...

Abstract A nonparametric method for comparing multiple forecast models is developed and implemented. The hypothesis of Optimal Predictive Ability generalizes the Superior Predictive Ability hypothesis from a single given loss function to an entire class of loss functions. Distinction is drawn...

A methodology is developed for constructing robust forecast combinations which improve upon a given benchmark specification for all symmetric and convex loss functions. The optimal forecast combination asymptotically almost surely dominates the benchmark and, in addition, minimizes the expected...

We analyze the value of foresight in the drybulk freight market when repositioning a vessel through space and time. In order to do that, we apply an optimization model on a network with dynamic regional freight rate differences and stochastic travel times. We evaluate the value of the...

How do we generate accurate predictions about the timely advancement of clinical trials? We report the methods and results of the first study comparing machine modeling and human crowdsourcing methods in clinical trial prediction. The study spans two 6-month tournaments that focus on trial phase...

This study introduces a Conditional Fuzzy inference (CF) approach in forecasting. The proposed approach is able to deduct Fuzzy Rules (FRs) conditional on a set of restrictions. This conditional rule selection discards weak rules and the generated forecasts are based only on the most powerful...