© 1987 by Biometrika Trust
A fast scoring algorithm for maximum likelihood estimation in unbalanced mixed models with nested random effects
Research Statistics Group, Educational Testing Service Princeton, New Jersey 08541, U.S.A.
A fast Fisher scoring algorithm for maximum likelihood estimation in unbalanced mixed models with nested random effects is described. The algorithm uses explicit formulae for the inverse and the determinant of the covariance matrix, given by LaMotte (1972), and avoids inversion of large matrices. Description of the algorithm concentrates on computational aspects for large sets of data.
Key Words: Fisher scoring algorithm • Maximum likelihood estimation • Nested random effects • Variance component
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