Cubature is the business of describing a probability measure in terms of an empirical measure sharing its support with the original measure, of small support, and with identical integrals for a class of functions (eg polynomials with degree less than k).
Applying cubature to already discrete sets of scenarios provides a powerful tool for scenario management and summarising data. We refer to this process as recombination. It is a feasible operation in real time and has lead to high accuracy pde solvers.
The practical complexity of this operation has changed! By a factor corresponding to the dimension of the space of polynomials.
We discuss the algorithm and give home computed examples of nested sparse grids with only positive weights in moderate dimensions (eg degree 1-8 in dimension 7). Positive weights have significant advantage over signed ones when available.
- Stochastic Analysis Seminar