estimate_SEG_params: Estimate SEG model parameters

In BruceKendall/PVA: Population viability analysis in R

Description

Given a time series of abundances, this function gives estimates and confidence intervals for the parameters of the stochastic exponential growth (SEG) parameters. It uses the "linear regression approach" described on pp. 120-121 of Dennis et al. (1991) (see also Chapter 3 of Morris & Doak 2002 for a friendlier description). By default, the time series of abundances is assumed to be equally spaced in time, with a timestep of one time unit; deviations from this can be accomodated by providing a vector of times associated with each abundance estimate.

Usage

estimate_SEG_params(Nt, Yeart = seq(along = Nt), alpha = 0.05)

Arguments

Nt	Time series of abundance. Must be a numeric vector of positive values, with length at least 3
Yeart	Sequence of times ("years") at which abundance is estimated (must be the same length as Nt). If the abundance estimates are available at each time step, this can be omitted
alpha	Significance level for confidence levels (default is 0.05).

Value

A list with the following elements:

mu	Estimate of the mean growth rate
sigma2	Estimate of the variance in the growth rate
params.CI	A matrix with the CI of mu in the first row and the CI of sigma2 in the second row
alpha	The alpha level passed in by the user

References

Dennis, B., Munholland, P. L. and Scott, J. M. (1991) Estimation of growth and extinction parameters for endangered species. Ecological Monographs 61, 115–143.

Morris, W. F. and Doak D. F. (2002) Quantitative Conservation Biology: Theory and Practice of Population Viability Analysis. Sunderland: Sinauer Associates.

Examples

data(grizzly)
estimate_SEG_params(grizzly$N)
  

BruceKendall/PVA documentation built on Jan. 23, 2021, 2:56 a.m.