Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

Forecast combinations have flourished remarkably in the forecasting community and, in
recent years, have become part of mainstream forecasting research and activities …

The increasing availability of satellite data at higher spatial, temporal and spectral
resolutions is enabling new applications in agriculture and economic development …

Water | Free Full-Text | Review: Sources of Hydrological Model Uncertainties and Advances
in Their Analysis Next Article in Journal Assessing the Influence of Compounding Factors to …

A valuable overview of the most important ideas and results in statistical modeling Written by
a highly-experienced author, Foundations of Linear and Generalized Linear Models is a …

Bayesian inference has found widespread application and use in science and engineering
to reconcile Earth system models with data, including prediction in space (interpolation) …

The method of model averaging has become an important tool to deal with model
uncertainty, for example in situations where a large amount of different theories exist, as are …

In ecology, the true causal structure for a given problem is often not known, and several
plausible models and thus model predictions exist. It has been claimed that using weighted …

Purpose Previous studies that dealt with corporate governance have witnessed gradually
significant growth that created some new trends. The purpose of this paper is to be involved …

Deviance Information Criterion: 12 Years on | Journal of the Royal Statistical Society Series B:
Statistical Methodology | Oxford Academic Skip to Main Content Advertisement Oxford …