The user specifies the probability of staying in the same area and spatial heterogeneity (both in the unfished state).
getmov2(x, Prob_staying, Frac_area_1)
A position in vectors Prob_staying and Frac_area_1
User specified probability that individuals in area 1 remain in that area (unfished conditions)
User specified fraction of individuals found in area 1 (unfished conditions)
A markov movement matrix
This is paired with movfit to find the correct movement model.
Prob_staying<-0.8 # probability that individuals remain in area 1 between time-steps Frac_area_1<-0.35 # the fraction of the stock found in area 1 under equilibrium conditions markovmat<-getmov2(1,Prob_staying, Frac_area_1) vec<-c(0.5,0.5) # initial guess at equilibrium distribution (2 areas) for(i in 1:300)vec<-apply(vec*markovmat,2,sum) # numerical approximation to stable distribution c(markovmat[1,1],vec) # pretty close right? #>  0.7999999 0.3500000