The function
L = \sum_{i=1}^b \sum_{j=1}^k (y_ij - \beta_i - \mu_j)^2
is given. The task is to differentiate it with respect to all b times k
parameters (which isn't very difficult) and use it to calculate the
estimates for all the \beta_i's and \mu_j's.
Any suggestions on how to do that? I've tried different approaches but the
\beta somehow always gets canceled out and nothing fun comes out of my
calculations...
--
Kindly
Konrad
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their souls be chased by demons in Gehenna from one room to
another for all eternity and more.
Sleep - thing used by ineffective people
as a substitute for coffee
Ambition - a poor excuse for not having
enough sense to be lazy
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