Berndt–Hall–Hall–Hausman algorithm

This approximation is based on the information matrix equality and therefore only valid while maximizing a likelihood function.

[2] If a nonlinear model is fitted to the data one often needs to estimate coefficients through optimization.

is a parameter (called step size) which partly determines the particular algorithm.

For the BHHH algorithm λk is determined by calculations within a given iterative step, involving a line-search until a point βk+1 is found satisfying certain criteria.

The BHHH algorithm has the advantage that, if certain conditions apply, convergence of the iterative procedure is guaranteed.