plot.Remigration: Plot the remigration intervals. In phenology: Tools to Manage a Parametric Function that Describes Phenology and More

 plot.Remigration R Documentation

Plot the remigration intervals.

Description

Plot the remigration intervals.

Usage

``````## S3 method for class 'Remigration'
plot(x, legend = TRUE, ...)
``````

Arguments

 `x` Object obtained from Bayesian.remigration() `legend` TRUE or FALSE or c(x, y) `...` Parameters transmitted to plot

Details

plot.Remigration plots the remigration intervals.

Value

An invisible dataframe with values used for plotting.

Author(s)

Marc Girondot

Other Model of Remigration Interval: `Bayesian.remigration()`, `LnRI_norm()`, `RI()`

Examples

``````## Not run:
library(phenology)
# Example

# Each year a fraction of 0.9 is surviving
s <- c(s=0.9)
# Probability of tag retention; 0.8
t <- c(t=0.8)
# Time-conditional return probability - This is the true remigration rate
r <- c(r1=0.1, r2=0.8, r3=0.7, r4=0.7, r5=1)
# Capture probability
p <- c(p1=0.6, p2=0.6, p3=0.6, p4=0.6, p5=0.6)
# Number of observations for 400 tagged females after 1, 2, 3, 4, and 5 years
OBS <- c(400, 10, 120, 40, 20, 10)

kl_s <- length(s)
kl_t <- length(t)
kl_r <- length(r)
kl_p <- length(p)

pMCMC <- data.frame(Density=c("newdbeta", "newdbeta", rep("dunif", kl_r),
rep("newdbeta", kl_p), "dunif"),
Prior1=c(s, t, rep(0, kl_r), rep(0.2, kl_p), 0),
Prior2=c(0.02, 0.02, rep(1, kl_r), rep(0.08, kl_p), 10),
SDProp=c(0.05, 0.05, rep(0.05, kl_r), rep(0.05, kl_p), 0.05),
Min=c(0, 0, rep(0, kl_r), rep(0, kl_p), 0),
Max=c(1, 1, rep(1, kl_r), rep(1, kl_p), 10),
Init=c(s, t, r, p, 1), stringsAsFactors = FALSE,
row.names=c("s",
"t",
names(r),
names(p), "sd")
)
rMCMC <- Bayesian.remigration(parameters = pMCMC,
n.iter = 1000000,