Learn R Programming

PVAClone (version 0.1-7)

PVAClone-package: Population Viability Analysis with Data Cloning

Description

Likelihood based population viability analysis in the presence of observation error and missing data. The package can be used to fit, compare, predict, and forecast various growth model types using data cloning.

Arguments

Author

Khurram Nadeem, Peter Solymos

Maintainer: Peter Solymos <psolymos@gmail.com>

Details

The package implements data cloning based population viability analysis methodology developed by Nadeem and Lele (2012). This includes model estimation, model selection and forecasting of future population abundances for estimate the extinction risk of a population of interest.

pva: main function for model fitting.

model.select: main function for model model selection.

Growth models: gompertz, ricker, bevertonholt, thetalogistic, thetalogistic_D.

References

Nadeem, K., Lele S. R., 2012. Likelihood based population viability analysis in the presence of observation error. Oikos 121, 1656--1664.

See Also

pva

Examples

Run this code
if (FALSE) {
## model selection for data with missing observations
data(songsparrow)
## model without observation error
m1 <- pva(songsparrow, gompertz("none"), 2, n.iter=1000)
## model with Poisson observation error
m2 <- pva(songsparrow, gompertz("poisson"), 2, n.iter=1000)
## model with Poisson observation error is strongly supported
model.select(m1, m2)
}

Run the code above in your browser using DataLab