title: Asymptotic bias in information estimates and the exponential (Bell) polynomials.
abstract: We present a new derivation of the asymptotic correction for bias in the estimate of information from a finite sample. The new derivation reveals a relationship between information estimates and a sequence of polynomials with combinatorial significance, the exponential (Bell) polynomials, and helps to provide an understanding of the form and behavior of the asymptotic correction for bias.
authors: Department of Neurology and Neuroscience, Weill Medical College of Cornell University, New York City, New York 10021, USA.
authors: J D
authors: JD
authors: Victor
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D015982:Bias; D008959:Models, Neurological; D011336:Probability