In section 3.2, it talks about saturated models having as many parameters as observations, so how does this lead to saturated model is the perfect fit to the data? in other words, how does model having same no. of parameters as the observations, fit that data perfectly?
And 2ndly in the same section, under key information it states that \mu^_i = y_i, shouldn't it be
g(\mu^_i)=y_i?
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Last edited by a moderator: Aug 13, 2017