# hawk.dove: Analysis of hawk-dove game theoretic model In learnPopGen: Population Genetic Simulations & Numerical Analysis

## Description

This function performs numerical analysis of a discrete-time hawk-dove model in which "payoff" determines relative fitness in the population.

## Usage

 `1` ``` hawk.dove(p=c(0.01,0.99), M=NULL, time=100) ```

## Arguments

 `p` Starting frequency of hawk & dove phenotypes, respectively. Should correspond with the rows of `M`. If a single value is given then `p` will automatically be set to `p=c(p,1-p)`. `M` Payoff matrix. `M[i,j]` should contain the fitness of `i` when interacting with `j`. `time` Number of generations.

## Value

The function creates a two panel plot. The upper panel shows the relative frequencies of each of the two interacting phenotypes. The lower panel shows mean fitness of the population and of each morph through time.

The function also invisibly returns an object of class `"hawk.dove"` containing the frequencies of each strategy through time and their fitnesses. This object can be printed or re-plotted using corresponding `print` and `plot` methods. (See examples.)

## Author(s)

Liam Revell liam.revell@umb.edu

`freqdep`

## Examples

 ```1 2 3 4 5``` ``` hawk.dove(time=60) Payoff<-matrix(c(0.5,0.6,1.5,1.0),2,2) object<-hawk.dove(M=Payoff,time=60) print(object) plot(object) ```

### Example output

```Pay-off matrix:
hawk dove
hawk  0.6  1.5
dove  0.5  1.0
Pay-off matrix:
hawk dove
hawk  0.5  1.5
dove  0.6  1.0

Object of class "hawk.dove" consisting of the results of a
numerical analysis of the so-called Hawk-Dove model in which
fitness is assumed to be proportional to the payoff from
interactions between the two alternative strategies as given
by the matrix:
hawk dove
hawk  0.5  1.5
dove  0.6  1.0

To plot enter plot('object_name') at the command line
interface.
```

learnPopGen documentation built on May 21, 2019, 1 a.m.