On Estimating the Fisher Information Matrix in Nonlinear Regression Models
Ch. E. Minder, Gerhard Gillmann · International Journal of Applied Mathematics & Statistics/International journal of applied mathematics and statistics · 2011
Estimation problems in nonlinear regression situations are often most easily attacked using an iterative estimation procedure for the nonlinear parameters of the regression equation and re-estimating the linear parameters at each step of the iteration. This paper proposes a method to compute an estimate of the full observed Fisher information matrix for all parameters when using this approach for parameter estimation.