Age-Structured Population Dynamics Model

Implements discrete time deterministic and stochastic age-structured population dynamics models described in Erguler and others (2016) and Erguler and others (2017) .


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))

News

Reference manual

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install.packages("albopictus")

0.5 by Kamil Erguler, 9 months ago


https://github.com/kerguler/albopictusR


Browse source code at https://github.com/cran/albopictus


Authors: Kamil Erguler [aut, cre]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports methods


See at CRAN