Maximum Entropy and the Moment Problem

The trigonometric moment problem stands at the source of many major streams in analysis. Here we use it to show that maximum entropy and maximum likelihood spectral estimation for stationary time series can be understood in terms of an elementary finite-dimensional orthogonal decomposition. This approach also characterizes each of these estimates as the solution of an extremal problem in Hilbet space.