<Para ID="Par1">Remote sensing technology for the study of Earth and its environment has led to “Big Data” that, paradoxically, have global extent but may be spatially sparse. Furthermore, the variability in the measurement error and the latent process error may not fit conveniently into the Gaussian linear...</para>

A prediction model is any statement of a probability distribution for an outcome not yet observed. This study considers the properties of weighted linear combinations of n prediction models, or linear pools, evaluated using the conventional log predictive scoring rule. The log score is a concave...

The predictability of stock market returns has been a challenge to market practitioners and financial economists. This is also important to central banks responsible for monitoring financial market stability. A number of variables have been found as predictors of future stock market returns with...

In this work, we present an aeroelastic model intended for three-blade large-scale horizontal-axis wind turbines. This model results from the coupling of an existing aerodynamic model and a structural model based on a segregated formulation derived in an index-based notation that enables...

This paper examines the influence of two major aspects on the solution quality of surrogate model algorithms for computationally expensive black-box global optimization problems, namely the surrogate model choice and the method of iteratively selecting sample points. A random sampling strategy...