2. (A variation of WrightFisher model) Similar to Problem 1, consider a model of a population with constant size N and types E = {1,2}. Let Xn be the number of type 1 individuals at time n. The evolution is now changed to: there is a parameter u E (0, 1), the distribution of X n+1 is Binomial (N, 11% + {1 u) (1 %)) conditioned on the event X\" = k, k E {0, 1,... , N}. Observe that 0, N are not absorbing state; for this chain. (i) Show that the Markov chain (Kn) converges to its unique stationary dis tribution arr. (Hint: Apply the convergence theorem, you do not need to compute the stationary distribution.) (ii) Compute limn mo <: for e ...>