Optimization function to find a movement model that matches user specified movement characteristics modified for Rcpp.

The user specifies the probability of staying in the same area and spatial heterogeneity (both in the unfished state).

Usage

getmov2(x, Prob_staying, Frac_area_1)

Arguments

x: A position in vectors Prob_staying and Frac_area_1
Prob_staying: User specified probability that individuals in area 1 remain in that area (unfished conditions)
Frac_area_1: User specified fraction of individuals found in area 1 (unfished conditions)

Value

A markov movement matrix

Details

This is paired with movfit to find the correct movement model.

Author

T. Carruthers

Examples


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[1]) # pretty close right?
#> [1] 0.7999999 0.3500000