  We discuss the problems of applying Maximum Likelihood methods to the CMB and
how one can make it both efficient and optimal. The solution is a generalised
eigenvalue problem that allows virtually no loss of information about the
parameter being estimated, but can allow a substantial compression of the data
set. We discuss the more difficult question of simultaneous estimation of many
parameters, and propose solutions. A much fuller account of most of this work
is available (Tegmark, Taylor & Heavens 1997)
