secder {demogR} | R Documentation |
secder
Description
Calculates the second derivatives of the dominant eigenvalue of the demographic projection matrix for all non-zero transitions with respect to one specified transition.
Usage
secder(A, k, l)
Arguments
A |
demographic projection matrix |
k |
row index for the specified transition |
l |
column index for the specified transition |
Details
See Caswell (1996, 2001) for details on second derivatives of the dominant eigenvalue.
Value
A square matrix of the same rank as A where each element s_{ij}
is the
second derivative of the dominant eigenvalue of A, \partial^2
\lambda/\partial a_{ij} \partial a_{kl}
.
Note
The eigenvalue second derivatives are essential for calculating both
perturbation analyses of the eigenvalue elasticities and stochastic
sensitivities. secder
is used in functions to calculate both
these quantities.
References
Caswell, H. 1996. Second derivatives of population growth rate: Calculation and applications. Ecology 77 (3):870-879.
Caswell, H. 2001. Matrix population models: Construction, analysis, and interpretation. 2nd ed. Sunderland, MA: Sinauer.
See Also
fullsecder
, elassens
,
eigen.analysis
, stoch.sens
Examples
## eigenvalue second derivatives of the US projection matrix from 1967
## with respect to infant survival
data(goodman)
ult <- with(goodman, life.table(x=age, nKx=usa.nKx, nDx=usa.nDx))
mx <- goodman$usa.bx/goodman$usa.nKx
usa <- leslie.matrix(lx=ult$nLx,mx=mx)
sd21 <- secder(usa,2,1)