Victor J D
Department of Neurology and Neuroscience, Weill Medical College of Cornell University, New York City, New York 10021, USA.
Neural Comput. 2000 Dec;12(12):2797-804. doi: 10.1162/089976600300014728.
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.
我们给出了一种新的推导方法，用于对有限样本中信息估计的偏差进行渐近校正。新的推导揭示了信息估计与具有组合意义的多项式序列（指数（贝尔）多项式）之间的关系，并有助于理解偏差渐近校正的形式和行为。
