e.single: calculate Elo ratings for a single interaction

Description Usage Arguments Value Author(s) References Examples

View source: R/e.single.R

Description

calculate Elo ratings for a single interaction

Usage

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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

Author(s)

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

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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.