# e.single: calculate Elo ratings for a single interaction In EloRating: Animal Dominance Hierarchies by Elo Rating

## Description

calculate Elo ratings for a single interaction

## Usage

 `1` ```e.single(ELO1old, ELO2old, outcome, k = 100) ```

## Arguments

 `ELO1old` Elo rating of the first individual `ELO2old` Elo rating of the second individual `outcome` "1" = first individual wins and second looses "2" = second individual wins and first looses "0" = interaction ends in a draw/tie (no winner and no looser) `k` k factor

## Value

length of vector 2 with updated ratings after the interaction of first and second individual

Christof Neumann

## References

Albers, P. C. H. & de Vries, H. 2001. Elo-rating as a tool in the sequential estimation of dominance strengths. Animal Behaviour, 61, 489-495.

Neumann, C., Duboscq, J., Dubuc, C., Ginting, A., Irwan, A. M., Agil, M., Widdig, A. & Engelhardt, A. 2011. Assessing dominance hierarchies: validation and advantages of progressive evaluation with Elo-rating. Animal Behaviour, 82, 911-921.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```e.single(ELO1old=1200, ELO2old=1000, outcome=1, k=100) # same as before e.single(ELO1old=1000, ELO2old=1200, outcome=2, k=100) # an undecided interaction e.single(ELO1old=1200, ELO2old=1000, outcome=0, k=100) # if rating differences are too big, no change occurs # if higher-rated individual wins e.single(ELO1old=2000, ELO2old=1000, outcome=1, k=100) # same as before but lower-rated individual wins and # therefore wins maximum number of points possible (i.e. k) e.single(ELO1old=2000, ELO2old=1000, outcome=2, k=100) ```

EloRating documentation built on May 29, 2017, 7:14 p.m.