Self-similarity of mathematical likelihood

Abstract

We study sufficiency in terms of the extent to which the Taylor series expansion of the normed log-likelihood function generated by the sampling distribution of a statistic conforms to that of the sample normed log-likelihood function, and give an associated self-similar property of mathematical likelihood (not self-similarity in the sense of self-similar stochastic processes).