perturb_stochastic: Calculate stochastic elasticities from a time-series of...

In Rage: Life History Metrics from Matrix Population Models

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 <[e-mail]>

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)

Rage documentation built on Sept. 30, 2023, 1:06 a.m.