Calculate stochastic elasticities from a time-series of matrix population models and corresponding population vectors
Calculate stochastic elasticities given a time-series of matrix population models and corresponding population vectors, using the method described in Haridas et al. (2009).
perturb_stochastic(X_t, u_t)
X_t |
A list of matrix population models |
u_t |
A list of corresponding population vectors |
A list of three matrices:
E |
matrix of stochastic elasticities |
E_mu |
matrix of stochastic elasticities to mean transition rates |
E_sigma |
matrix of stochastic elasticities to the variance in transition rates |
Patrick Barks <patrick.barks@gmail.com>
Haridas, C. V., Tuljapurkar, S., & Coulson, T. 2009. Estimating stochastic elasticities directly from longitudinal data. Ecology Letters, 12, 806-812. <doi:10.1111/j.1461-0248.2009.01330.x>
Other perturbation analysis:
perturb_matrix()
,
perturb_trans()
,
perturb_vr()
,
pop_vectors()
# generate list of random MPMs N <- 20 # number of years s <- 3 # matrix dimension X <- list() # matrix population model at time t u <- list() # population vector at time t for(t in 1:N) { X[[t]] <- matrix(runif(s^2), nrow = s, ncol = s) } # derive corresponding series of population vectors u <- pop_vectors(X) # calculate stochastic elasticities perturb_stochastic(X, u)
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