A stochastic version of the Verhulst-Pearl logistic model.
This evolves in continuous time, according to the stochastic differential equation
$$dn_t = r\,n_t\,\left(1-\frac{n_t}{K}\right)\,dt+\sigma\,n_t\,dW_t.$$
Numerically, we simulate the stochastic dynamics using an Euler approximation.
The measurements are assumed to be log-normally distributed:
$$N_t \sim \mathrm{Lognormal}\left(\log{n_t},\tau\right).$$