While process modeling is useful, a user might like to export 3D models (built during process simulation) out of the purely physical modeling domain and into other simulation domains, such as ...

We study counting process models for event history data where the intensities depend on unobservable quantities ("frailties"). Examples include models for dependent failure times and regression models ...

Robert E. Kass, Ryan C. Kelly, Wei-Liem Loh, ASSESSMENT OF SYNCHRONY IN MULTIPLE NEURAL SPIKE TRAINS USING LOGLINEAR POINT PROCESS MODELS, The Annals of Applied Statistics, Vol. 5, No. 2B (June 2011), ...

As climate change and population growth increase pressure on global food production, regional-scale crop growth and associated process (CROP-AP) models have become essential tools for ...

An operations planning and economics improvement project at ConocoPhillips's Lake Charles, La., refinery successfully developed and implemented high-quality kinetic process models used for unit ...

The process models really lay the foundation for process maturity,however, the SW Industry needs a new rating method that is reliable and economical ...

When modelers encounter difficulties with random effects, it is usually for one of two reasons. Either they ignore the random effects completely or they model them as fixed parameters.