Matlab Algorithm Mixed.M for Solving Henderson's Mixed Model Equations

The MATLAB algorithm mixed.m estimates the parameters of the mixed linear model by using the Henderson's MMEs (mixed model equations) algorithm, for more details see Searle et al. (1992, pp. 275-286).The algorithm computes the BLUE or the two-stage GLSE, the BLUP or the EBLUP, and the ML, REML, MINQE(I), or MINQE(U,I) of the fixed effects, the random effects, and the variance components, respectively, in the mixed linear model, together with the generalized inverse of the MMEs coefficient matrix and the Fisher information matrix for the estimated variance components. This allows the user to make the statistical inference (which is at least asymptotically correct) on the set of linear combinations of the fixed effects ′ (by using its BLUE or the two-stage GLSE) and/or on the set of linear combinations of the fixed and the random effects ′ + ′ (by using its BLUP or EBLUP), whenever ′ is a vector of linearly estimable functions of the elements of the fixed effects vector .The presented MATLAB algorithm mixed.m was written as a flexible tool for my own research and educational purposes. It was not intended, in any sense, to become an alternative to the professional statistical packages, like e.g. SAS (Proc MIXED) or S-plus (nlme library), which deal with the mixed linear models on more sophisticated and complex level.The algorithm mixed.m is available at http://www.mathworks.com/ matlabcentral/fileexchange, see the Statistics Category