In statistics, additive smoothing, also called Laplace smoothing[1] (not to be confused with Laplacian smoothing as used in image processing), or Lidstone smoothing, is a technique used to smooth categorical data. Given an observation x = ⟨ x 1 , x 2 , … , x d ⟩ {\textstyle \scriptstyle {\mathbf {x} \ =\ \left\langle x_{1},\,x_{2},\,\ldots ,\,x_{d}\right\rangle }} from a multinomial distribution with N {\textstyle \scriptstyle {N}} trials, a "smoothed" version of the data gives the estimator: