Creating the Gaussian process regression model is simultaneously simple and complicated. The code is relatively short: # 2. create and train GPR model print ... loaded_model = pickle.load(f) X = (set ...

Hence, the total serial time to run the regressions was roughly 10,000 hours. However, the regression runs on a grid system, thus, taking 20 parallel machines into consideration, the ideal regression ...

Duration: 12h. In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial ...

The process of minimizing RSS through least squares regression involves iteratively adjusting the parameters of the model. This is usually done until the optimal fit is achieved.

Our approach avoids nested simulation or simulation and regression of cashflows by learning a Gaussian metamodel for the mark-to-market cube of a derivative portfolio. We model the joint posterior of ...