02Caswell: Converted Matlab functions from Caswell (2001)
In popbio: Construction and Analysis of Matrix Population Models

02.Caswell

R Documentation

Converted Matlab functions from Caswell (2001)

Chapter 2. Age-classified matrix models

Chapter 4. Stage-classified matrix models

lambda: section 4.4. Returns the dominant eigenvalue
stable.stage: section 4.5. Returns the stable stage distribution (right eigenvector)
reproductive.value: section 4.6. Returns the reproductive value (left eigenvector)
damping.ratio: section 4.7. Returns the damping ratio
eigen.analysis: section 4.8. Computes eigenvalues and vectors, including the dominant eigenvalue , stable stage distribution, reproductive value, damping ratio, sensitivities, and elasticities. Since version 2.0, these are now included as separate functions as well

Chapter 5. Events in the Life Cycle

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

Age-specific survivorship and fertility curves in Fig 5.1 and 5.2 are now included in demo(Caswell).

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.

Chapter 9. Sensitivity analysis

Chapter 10. Life Table Response Experiments

LTRE: section 10.1 and 10.2. Fixed designs in LTREs. See demo(Caswell) for variance decomposition in random design (Fig 10.10).

Chapter 12. Statistical inference

boot.transitions: section 12.1.4. Resample observed census transitions in a stage-fate data frame
resample: section 12.1.5.2. Resample transitions in a projction matrix from a multinomial distribution (and fertilites from a log normal)

Chapter 14. Environmental stochasticity

stoch.growth.rate: section 14.3. Calculate the log stochastic growth rate by simulation and Tuljapukar's approximation
stoch.sens: section 14.4.1. Senstivity and elasticity of stochastic growth rate from numerical simultations
stoch.projection: section 14.5.3. Project stochastic growth from a sequence of matrices in a uniform and nonuniform environment

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.