Model complexity in amplitude analyses is often a priori under-constrained
since the underlying theory permits a large number of possible amplitudes to
contribute to most physical processes. The use of an overly complex model
results in reduced predictive power and worse resolution on unknown parameters
of interest. Therefore, it is common to reduce the complexity by removing from
consideration some subset of the allowed amplitudes. This paper studies a
method for limiting model complexity from the data sample itself through
regularization during regression in the context of a multivariate (Dalitz-plot)
analysis. The regularization technique applied greatly improves the
performance. An outline of how to obtain the significance of a resonance in a
multivariate amplitude analysis is also provided
