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General development of GLMâs The modeling assumptions for a GLM are I The Yi are conditionally independent given X . I The probability mass function or density can be written log p(Yi |θi , Ï, Xi ) = wi (Yi θi â γ(θi ))/Ï + Ï (Yi , Ï/wi ), where wi is a known weight, θi = g (β 0 Xi ) for an unknown vector of regression slopes β, g (·) and γ(·) are smooth functions, Ï is the âscale parameterâ (which may be either known or unknown), and Ï (·) is a known function. 17 / 35
