Learn R Programming

fishmove (version 0.3-3)

pdk: Plotting Probability Dispersal Kernel (pdk) of Fish Movement

Description

Plotting probability dispersal Kernel (pdk) of fish movement based on multiple regression

Usage

pdk(fishmove, p = 0.67,...)

Arguments

fishmove
Output from fishmove, containing the movement parameters $sigma_stat$ and $sigma_mob$.
p
Share of stationary component on the population (0-1). The default value for p is 0.67.
...
do not use.

Details

pdk provides graphs (based on ggplot2) displaying probability density kernels (pdk) for leptokurtic fish dispersal. For each plot the fitted mean as well as the upper and the lower bound (based on confidence or prediction interval, see predict.lm) are displayed.

p is the share of the stationary component in the population resp. 1-p is the share of the mobile component. An average value for p is 0.66 (66% stationary) (Radinger and Wolter, 2013).

The underlying leptokurtic density function is:

$$ F(x)=p*\frac{1}{\sqrt{2\pi\sigma_{stat}^2}}*e^{-\frac{(x-\mu)^2}{2\sigma_{stat}^2}}+(1-p)*\frac{1}{\sqrt{2\pi\sigma_{mob}^2}}*e^{-\frac{(x-\mu)^2}{2\sigma_{mob}^2}}$$

References

Radinger, J. and Wolter C. (2014) Patterns and predictors of fish dispersal in rivers. Fish and Fisheries. 15:456-473. DOI: http://dx.doi.org/10.1111/faf.12028.

See Also

fishmove, lm, predict.lm, ggplot

Examples

Run this code
	# Plotting dispersal kernel for selected fish species with time=365 days
	pdk(fishmove(species="Salmo trutta fario",T=365))

Run the code above in your browser using DataLab