"We're taking a resume, we're building a statistical model around that resume, abstracting it out and the same for the job descriptions," Goodman said.
A statistical emulator is a fast proxy for a complex computer model which predicts model output at arbitrary parameter settings from a limited ensemble of training data.
It involves running a consequence model around a hundred times and using the results to construct a statistical emulator, which is essentially a sophisticated curve fit to the data.
However, from what I can glean from the team, it's the same kind of problem: implementing a parametric Bayesian analysis with a computationally expensive model, by building a fast nonparametric "emulator" for the model.
Secondly, we build a statistical approximation to the output of the computer model, known as a Gaussian process emulator.
And corresponding statistical model, including two computing formulas for single building and a statistical method for regional buildings was designed.
Building national statistical capacity will be an integral part of this work.
For computationally expensive models, model evaluation time may preclude an extensive sampling of the input space, and the development of statistical emulators (Santner et al. 2003; Rougier 2008; Bayarri et al. 2009; Vernon et al. 2010; Lee et al. 2011) or fast surrogate models (Bursik et al. 2012; Madankan et al. 2014) may be necessary.
This leads to an efficient emulator that, due to the consideration of our knowledge about dominant mechanisms built into the simulation model, can be expected to outperform purely statistical emulators at least in cases in which the design data set is small.
Coupling Computer Models through Linking their Statistical Emulators, with KN Kyzyurova & JO Berger.
