Description
Age-Structured Population Dynamics Model.
Description
Implements discrete time deterministic and stochastic age-structured population dynamics models described in Erguler and others (2016) <doi:10.1371/journal.pone.0149282> and Erguler and others (2017) <doi:10.1371/journal.pone.0174293>.
README.md
albopictus
Age-Structured Population Dynamics Model
Installation
The R package can be installed from the command line,
R CMD install albopictus_x.x.tar.gz
to be loaded easily at the R command prompt.
library(albopictus)
Usage
Generate a population with stochastic dynamics
s <- spop(stochastic=TRUE)
Add 1000 20-day-old individuals
add(s) <- data.frame(number=1000,age=20)
Iterate one day without death and assume development in 20 (+-5) days
iterate(s) <- data.frame(dev_mean=20,dev_sd=5,death=0)
print(developed(s))
Iterate another day assuming no development but age-dependent survival. Let each individual survive for 20 days (+-5)
iterate(s) <- data.frame(death_mean=20,death_sd=5,dev=0)
print(dead(s))
Note that the previous values of developed and dead will be overwritten by this command
Generate a deterministic population and observe the difference
s <- spop(stochastic=FALSE)
add(s) <- data.frame(number=1000,age=20)
iterate(s) <- data.frame(dev_mean=20,dev_sd=5,death=0)
print(developed(s))
iterate(s) <- data.frame(death_mean=20,death_sd=5,dev=0)
print(dead(s))