This function finds the best estimates of mean and environmental variance for beta-binomial vital rates, using the approximation method of Akcakaya (2002).
varEst(rates, weighted=1)
a matrix or dataframe with four columns: Rate identifier, Year, Total number of starting individuals, Number surviving (or growing)
either 1 for weighted average demographic variance, or 0 for unweighted average, default is 1.
A matrix with 3 columns: (1) total observed variance, (2) estimate of variance due to demographic stochasticity, and (3) estimate of variance due to environmental stochasticity.
Akcakaya, H. R. 2002. Estimating the variance of survival rates and fecundities. Animal Conservation 5: 333-336.
Kendall, B. E. 1998. Estimating the magnitude of environmental stochasticity in survivorship data. Ecological Applications 8(1): 184-193.
# NOT RUN {
data(woodpecker)
varEst(woodpecker)
# }
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