Abstract
SUMMARY A linearization theorem represents an estimating equation for an unknown parameter as approximately linear in the neighbourhood of the true parameter point, and can provide a convenient approach to asymptotic theory. A multiparameter version of a standard linearization theorem is proved, and applied to two examples: M-estimates in multiple regression, and the spherical median.
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