My instinct is that we should still figure out an appropriate transformation for the error distribution (currently Gaussian with mean 0). Otherwise, any negative hospitalization count produced by f(i) + ε, ε ~ N(μ, σ^2) gets transformed to 0, and we lose the random error.
I suspect the goal should be this: 0.5 * [|f(i)| + f(i)] + ε, ε ~ dist(x).
On the other hand, we know counts during the early season will be near zero.
My instinct is that we should still figure out an appropriate transformation for the error distribution (currently Gaussian with mean 0). Otherwise, any negative hospitalization count produced by
f(i) + ε, ε ~ N(μ, σ^2)
gets transformed to 0, and we lose the random error.I suspect the goal should be this:
0.5 * [|f(i)| + f(i)] + ε, ε ~ dist(x)
.On the other hand, we know counts during the early season will be near zero.