  Extended dynamic mode decomposition (EDMD) is a data-driven algorithm for
approximating spectral data of the Koopman operator associated to a dynamical
system, combining a Galerkin method of order N and collocation method of order
M. Spectral convergence of this method subtly depends on appropriate choice of
the space of observables. For chaotic analytic full branch maps of the
interval, we derive a constraint between M and N guaranteeing spectral
convergence of EDMD.
