perturb_stochastic {Rage} | R Documentation |
Calculate stochastic elasticities from a time-series of matrix population models and corresponding population vectors
Description
Calculate stochastic elasticities given a time-series of matrix population models and corresponding population vectors, using the method described in Haridas et al. (2009).
Usage
perturb_stochastic(X_t, u_t)
Arguments
X_t |
A list of matrix population models |
u_t |
A list of corresponding population vectors |
Value
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 |
Author(s)
Patrick Barks <patrick.barks@gmail.com>
References
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>
See Also
Other perturbation analysis:
perturb_matrix()
,
perturb_trans()
,
perturb_vr()
,
pop_vectors()
Examples
# 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)