02.Caswell {popbio} | R Documentation |
Converted Matlab functions from Caswell (2001)
Description
Chapter 2. Age-classified matrix models
-
pop.projection
- section 2.2. Projection of
population growth rates. See
stage.vector.plot
to
plot stage (or age) vectors
Chapter 4. Stage-classified matrix models
-
eigen.analysis
- section 4.8. Computation of
eigenvalues and eigenvectors. Returns the dominant eigenvalue
(section.4.4), stable stage distribution (section 4.5),
reproductive value (section 4.6), and damping ratio (section 4.7)
Chapter 5. Events in the Life Cycle
-
whale
- Figures 5.1 and 5.2. The example
includes code to calculate age-specific
survivorship and fertility curves.
-
fundamental.matrix
- section 5.3.1.
Calculate age-specific survival from a stage classified matrix
using the fundamental matrix N
-
net.reproductive.rate
- section 5.3.4.
Calculate the net reproductive rate of a stage classified matrix
using the dominant eigenvalue of the matrix R.
-
generation.time
- section 5.3.5. Calculate the
generation time of a stage-classified matrix
Chapter 6. Parameter estimation
-
projection.matrix
- section 6.1.1. Estimate
vital rates and construct a projection matrix using transtion
frequency tables
-
QPmat
- section 6.2.2. Construct a projection
matrix from a time series of individuals per stage using Wood's
quadratic programming method. Requires
quadprog
library.
See the Rcapture
package for capture-recapture methods
described in section 6.1.2.
Chapter 9. Sensitivity analysis
-
eigen.analysis
- section 9.1, and 9.2.
Calculate sensitivities and elasticities. The examples in the
teasel and tortoise datasets also include code to
sum elasticities and create figures like 9.3, 9.4, and 9.11.
See the secder
function in the demogR
package for second derivatives of eigenvalues
described in section 9.7
Chapter 10. Life Table Response Experiments
-
LTRE
- section 10.1 and 10.2. Fixed designs in
LTREs. The example includes code for variance
decomposition in random design.
Chapter 12. Statistical inference
-
boot.transitions
- section 12.1.5.5.
Methods to bootstrap observed census transitions and calculate
confidence intervals using
quantile
Chapter 14. Environmental stochasticity
-
stoch.growth.rate
- section 14.3. Calculate the
log stochastic growth rate by simulation and Tuljapukar's approximation
-
stoch.projection
- section 14.5.3. Project
stochastic growth from a sequence of matrices in a uniform and
nonuniform environment
See the stoch.sens
function in the demogR
package for senstivity and elasticity of log
stochastic growth rate described in section 14.4.
Chapter 15. Demographic stochasticity
-
multiresultm
- section 15.1.3. Incorporate
demographic stochasticity into population projections. The
example uses the whale dataset to create a plot like figure
15.3.
Author(s)
Chris Stubben
[Package
popbio version 1.1.11
Index]