Check for convergence in *stochastic* lambda

[Aariq]

Right now it seems like it doesn't make sense to use conv_plot() or is_conv_to_asymptotic() on stochastic IPMs since both functions use the lambdas for each transition year. I'm not super familiar with the literature on this, but it makes intuitive sense to me that you'd want to check for convergence in the stochastic lambda. Couldn't you do this by checking for convergence after calculating a cumulative mean on all the lambdas?

[Aariq]

Just browsing through code from Ellner, Childs and Rees and they also check for convergence in stochastic lambda using a cumulative mean.

#how fast do they converge?

Ls.N <- cumsum(rt.N)/(1:n.est)
Ls.V <- cumsum(rt.V)/(1:n.est)

n.samp <- n.est

plot(Ls.N[1:n.samp],type="l")
points(Ls.V[1:n.samp],type="l",col="red")
abline(h=mean(rt.N))

Where rt.N = log(sum(nt1)/sum(nt)), which is the average annual growth rate, rt.V is an approximation of total reproductive value, and n.est is just the number of iterations.

[levisc8]

This has been addressed by #44, right?

[Aariq]

Yeah, this has been dealt with now.