We propose a family of copula-based multivariate distributions with g-and-h marginals. After studying the properties of the distribution, we develop a two-step estimation strategy and analyze via ...

We adapt a semi-Bayesian hierarchical modeling framework to jointly characterize the space–time variability of seasonal precipitation totals and precipitation extremes across the Northern Great Plains ...

Discover how Monte Carlo analysis helps investors assess risk and make informed decisions. Explore its role in generating ...

Innovators are increasingly focused on whether outsourced partners can help them make better decisions earlier, before ...

Extending the Eaves et al Markov model for genetically informative data to the multivariate case is described. At the time of writing, this model has not yet been implemented in a software script, so ...

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...