Good–Turing frequency estimation is a smoothing estimator for estimating a multinomial distribution. It seems very convoluted.

  1. From mathematical statistics point of view, what is the rationale behind the construction of Good–Turing frequency estimation?
  2. Is it a shrinkage estimator?
  3. Is it based on the posterior distribution with respect to some prior distribution on the parameters, in Bayesian inference view?
  4. Is it not additive smoothing, is it? What type of smoothing is it?

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