lams: lams
In demogR: Analysis of Age-Structured Demographic Models

Description Usage Arguments Details Value References See Also Examples

Calculates the logarithm of the stochastic growth rate using Tuljapurkar's second order approximation for independent and identically distributed environments.

1	lams(aseq, n = 5)

`aseq`	sequence of matrices with each matrix given as a re-shaped column of aseq
`n`	width of the projection interval/age-class

Uses Tuljapurkar's second order approximation for independent and identically distributed (i.i.d.) environments.

The long-run growth rate for the population with projection matrices given by aseq.

Tuljapurkar, S. 1990. Population dynamics in variable environments. Edited by S. A. Levin. Vol. 85, Lecture notes in biomathematics. Berlin: Springer-Veralg.

Caswell, H. 2001. Matrix population models: Construction, analysis, and interpretation. 2nd ed. Sunderland, MA: Sinauer.

stoch.sens, eigen.analysis

## simulate two matrices: good year/bad year
## beta distributed survival, gamma fertility

px1 <- rbeta(5,9,1)
px2 <- rbeta(5,7,3)
mx1 <- c(0,rgamma(5,10,10))
mx2 <- c(0,rgamma(5,7,10))
## good year matrix
A1 <- odiag(px1,-1)
A1[1,] <- mx1

## bad year matrix
A2 <- odiag(px2,-1)
A2[1,] <- mx2
aseq <- cbind(matrix(A1,nr=36,nc=1), matrix(A2,nr=36,nc=1))
lams(aseq)