Additional biomass estimation alternatives: nonlinear two- and three-stage least squares and full information maximum likelihood for slash pine

Iteratively Reweighted Least Squares for Maximum Likelihood Estimation, and some Robust and Resistant Alternatives

The scope of application of iteratively reweighted least squares to statistical estimation problems is considerably wider than is generally appreciated. It extends beyond the exponential-family-type generalized linear models to other distributions, to non-linear parameterizations, and to dependent observations. Various criteria for estimation other than maximum likelihood, including resistant a...

Origins of the limited information maximum likelihood and two-stage least squares estimators

Theil, Basmann, and Sargan are often credited with the development of the two-stage least squares (TSLS) estimator of the coefficients of one structural equation in a simultaneous equations model. However, Anderson and Rubin had earlier derived the asymptotic distribution of the limited information maximum likelihood (LIML) estimator by finding the asymptotic distribution of what is essentially...

Least squares and maximum likelihood

Estimation by Least Squares and by Maximum Likelihood

Although statements to the contrary are often made, application of the principle of least squares is not limited to situations in which p is normally distributed. The GaussMarkov theorem is to the effect that, among unbiased estimates which are linear functions of the observations, those yielded by least squares have minimum variance, and the independence of this property from any assumption re...

Maximum Likelihood Recursive Least Squares Estimation for Multivariable Systems

This paper discusses parameter estimation problems of the multivariable systems described by input–output difference equations. We decompose a multivariable system to several subsystems according to the number of the outputs. Based on the maximum likelihood principle, a maximum likelihood-based recursive least squares algorithm is derived to estimate the parameters of each subsystem. Finally, t...