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Consider how random effects are fitted #10

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@Aariq

Since there are several ways to include random effects for GAMs, it might be worthwhile thinking about which is best. A simple random intercept (s(year, bs = "re")) is probably what most demographers would do. A random smoother for each year (s(log_size_prev, year, bs = "fs")) is probably the best fit to the data. Ideas outlined in notes/environmental stochasticity.Rmd

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