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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))

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Version

Install

install.packages('albopictus')

Monthly Downloads

300

Version

0.5

License

GPL (>= 3)

Issues

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Stars

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Maintainer

Kamil Erguler

Last Published

November 29th, 2018

Functions in albopictus (0.5)

dead

Read dead
developed

Read developed
gamma_dist_prob

Gamma probability of death or development
devtable

Read devtable
spop

An S4 class to represent an age-structured population
add<-

Add batch
perturb<-

Iterate population without incrementing age or development
albopictus-package

Age-Structured Population Dynamics Model
size

Read size
iterate<-

Iterate population
nbinom_dist_prob

Negative binomial probability of death or development