Log-normal MCMCglmm

Hi Dani,

Can you explain with a formula what you mean by the difference between a model with log-normal errors and a model with normal errors where the response is log-transformed? As the errors are log-normal, i.e. strictly positive, they presumably can?t be additive. Are they multiplicative? If they are then logging the predictor will result in an additive model with normal errors.

E.g. a multiplicative model with lognormal errors:
Y = Yhat * exp(epsilon), where epsilon ~ exp(N(0, sigma^2))

Log it:
log(Y) = log(Yhat) + log(epsilon)
which is an additive model with normal errors with the response log-transformed.

Best wishes,
Paul

Log-normal MCMCglmm

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