Improving forecasting especially time series forecasting accuracy is an important yet often
difficult task facing decision makers in many areas. Combining multiple models can be an …

I briefly summarize prior research showing that tests of statistical significance are improperly
used even in leading scholarly journals. Attempts to educate researchers to avoid pitfalls …

Forecasting of time series that have seasonal and other variations remains an important
problem for forecasters. This paper presents a neural network (NN) approach to forecasting …

Inventory control systems typically require the frequent updating of forecasts for many
different products. In addition to point predictions, interval forecasts are needed to set …

The outcomes of matches in the 2005 Wimbledon Gentlemen's tennis competition were
predicted by mere player name recognition. In a field study, amateur tennis players (n= 79) …

We extend the standard approach to Bayesian forecast combination by forming the weights
for the model averaged forecast from the predictive likelihood rather than the standard …

This paper proposes a model of the US unemployment rate which accounts for both its
asymmetry and its long memory. Our approach introduces fractional integration and …

Accurate estimates of future age‐specific incidence and mortality are critical for allocation of
resources to breast cancer control programmes and evaluation of screening programmes …

This paper provides a formulation for the additive Holt–Winters forecasting procedure that
simplifies both obtaining maximum likelihood estimates of all unknowns, smoothing …

Effective supply chain management is one of the key determinants of success of today's
businesses. However, communication patterns between participants that emerge in a supply …