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]