# 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)

### Description

Chapter 2. Age-classified matrix models

`pop.projection`

section 2.2. Projection of population growth rates.

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

`sensitivity`

section 9.1. Calculate sensitivities

`elasticity`

section 9.2. Calculate elasticities

`secder`

section 9.7. Second derivatives of eigenvalues

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.

### Author(s)

Chris Stubben

popbio documentation built on May 29, 2024, 4:35 a.m.