pondfrog {blmeco} | R Documentation |
Fake Data of the Numbers of Frogs in Ponds
Description
The data contain frog population sizes in different ponds with some characteristics of ponds. The data is simulated, thus the "true" model is known. The data can serve to play with different methods for doing model selection.
Usage
data(pondfrog)
Format
A data frame with 130 observations on the following 9 variables.
frog
a numeric vector
fish
a numeric vector
vegdensity
a numeric vector
ph
a numeric vector
surfacearea
a numeric vector
waterdepth
a numeric vector
region
a factor with levels
north
south
height
a numeric vector
temp
a numeric vector
Details
The r-code for producing the pondfrog data is
set.seed(196453) n <- 130 # sample size height <- sample(150:1500,n) region <- sample(c("south", "north"), n, replace=TRUE, prob=c(0.2, 0.8)) waterdepth <- sample(seq(0.3, 5.5, by=0.01), n) surfacearea <- sample(seq(3, 150), n) temp <- 20 - 0.01*height + 0.5*as.numeric(region=="south") -0.005*waterdepth + 0.1*sqrt(surfacearea) +rnorm(n, 0, 1.5) ph <- 7.5 - 0.8 * as.numeric(region=="south") + rnorm(n, 0, 0.2) vegdensity.logitp <- -3.5+0.3*ph + 0.2*temp+rnorm(n,0,1) vegdensity.p <- plogis(vegdensity.logitp) vegdensity <- rbinom(n, 1, prob=vegdensity.p) fish.logitp <- -4+0.3*ph + 0.2*waterdepth+rnorm(n,0,1) fish.p <- plogis(fish.logitp) fish <- rbinom(n, 1, prob=fish.p) frog.mu <- exp(3.5 + 0.2*(temp-mean(temp)) +0.2*(ph-mean(ph)) + 0.1*(ph-mean(ph))^2 - 0.3*(waterdepth-mean(waterdepth)) - 0.5 * fish + 0.5*fish*vegdensity) frog <- rpois(n, lambda=frog.mu)
dat <- data.frame(frog=frog, fish=fish, vegdensity=vegdensity, ph=ph, surfacearea=surfacearea, waterdepth=waterdepth, region=region, height=height, temp=temp)
Thus, the "true" model for the number of pondfrog (frog) is a Poisson model with log-link function and the following linear predictor:
3.5 + 0.2*(temp-mean(temp)) +0.2*(ph-mean(ph)) + 0.1*(ph-mean(ph))^2 - 0.3*(waterdepth-mean(waterdepth)) - 0.5 * fish + 0.5*fish*vegdensity
Examples
data(pondfrog)
pairs(pondfrog)