Results on the PASCAL PROMO challenge
(University of Southampton, UK)
A solution to the PASCAL PROMO challenge “Simple causal effects in time series” is presented.
The data is modeled as a sum of a constant-plus-sin term (autonomous part) and a term that is a
linear function of a small number of inputs. The problem of identifying such a model from the data
is nonconvex in the frequency and phase parameters of the sin and is combinatorial in the number
of inputs. The proposed method is suboptimal and exploits several heuristics. First, the problem
is split into two phases: 1) identification of the autonomous part and 2) identification of the input
dependent part. Second, local optimization method is used to solve the problem in the first phase.
Third, l1 regularization is used in order to find a sparse solution in the second phase.