qsd_converge: Compute the quasi-stable trait distribution for a stochastic...

In levisc8/irage: Life History Analysis for Integral Projection Models

Description

Compute the quasi-stable trait distribution for a stochastic model

Usage

qsd_converge(ipm, p_nms, tol, start_life, n_steps, ...)

## S3 method for class 'simple_di_stoch_kern_ipm'
qsd_converge(
  ipm,
  p_nms,
  tol = 1e-07,
  start_life = rep(1, length(p_nms)),
  n_steps = 1000,
  ...
)

Arguments

ipm	The output from make_ipm
p_nms	The name of the survival/growth kernel(s)
tol	The distance between each kernels true eigenvector and the quasi-stable distribution that is acceptable. Computed as 0.5 * sum(abs(pop_size - right_ev)). Default is 1e-7
start_life	The index of the population vector to start on. Should be a named list where names correspond to population states and entries are length 1 integer vectors. Default is 1.
n_steps	The number of times to iterate the model before checking for convergence. Default is 1000.
...	other arguments passed to methods.

levisc8/irage documentation built on March 6, 2020, 12:56 a.m.