Maximum Likelihood Parameters

In these algorithms, the goal is to estimate hyperparameters using maximum likelihood.

Parameters

  • nn: number of observations in sample
  • rr: number of parameters + latent variables

Filters

Computational Model

Randomization

Approximation

Algorithms Table

Displaying 6 of 6 algorithms

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Expectation conditional maximization (ECM)2017O(n2logn)O(n^2 \log n)O(n+r)O(n+r)
α-EM algorithm2003O(n3)O(n^3)O(n+r)O(n+r)
Parameter-expanded expectation maximization (PX-EM) algorithm1998O(n3)O(n^3)O(n+r)O(n+r)
Generalized expectation maximization (GEM) algorithm1994O(n4log1.5n)O(n^4 \log^{1.5} n)O(n+r)O(n+r)
Expectation–maximization (EM) algorithm1977O(n3)O(n^3)O(n+r)O(n+r)
Newton–Raphson algorithm1685O(n3)O(n^3)O(n+r2)O(n+r^2)

Reductions Table

Insuffient Data to display table

Other relevant algorithms

Insuffient Data to display table