Recently I've found the Tweedie distribution useful for modelling my plant shoot weight data in glmmTMB. I started using it because my shoot weight datasets have many zeroes, and it has yielded better fits than I was able to get with zero-inflated models.
One of my shoot weight datasets doesn't have zeroes, however (although it does have many <1 values). The Gaussian distribution fits this dataset well enough, but I don't think that the predictions it makes are correct. I tried this model with the Tweedie distribution, and I got a better fit and predictions that make more sense.
Despite the good fit, is it invalid to use the Tweedie distribution when your data doesn't have zeroes? This is the code I'm using:
Model4 <- glmmTMB(Shoot.weight ~ Species + N.Level + Rhizobia + Species:N.Level + Species:Rhizobia + N.Level:Rhizobia + N.Level:Rhizobia:Species + (1 | Block), family = tweedie, data = SOY)
I believe that the specific Tweedie distribution that I'm using here is the compound Poisson-Gamma distribution, but correct me if I'm wrong about that.