  The normalized maximum likelihood code length has been widely used in model
selection, and its favorable properties, such as its consistency and the upper
bound of its statistical risk, have been demonstrated. This paper proposes a
novel methodology for calculating the normalized maximum likelihood code length
on the basis of Fourier analysis. Our methodology provides an efficient
non-asymptotic calculation formula for exponential family models and an
asymptotic calculation formula for general parametric models with a weaker
assumption compared to that in previous work.
