scale_elo: standardize Elo ratings
In EloRating: Animal Dominance Hierarchies by Elo Rating
Description
Usage
Arguments
Value
Author(s)
Examples
Description
standardize Elo ratings between 0 and 1
Usage
1
scale_elo(x)
Arguments
x
numeric, a vector of Elo ratings
Value
a numeric vector of Elo ratings, which are scaled between 0 and 1, with the highest rating that is supplied becoming 1, the lowest becoming 0, and all others being proportionally scaled in between
Author(s)
Christof Neumann
Examples
1
2
3
4
5
6
7
data(adv)
SEQ <- elo.seq(winner=adv$winner, loser=adv$loser, Date=adv$Date)
extract_elo(SEQ, "2010-01-30")
extract_elo(SEQ, "2010-01-30", standardize=TRUE)
# same as
scale_elo(extract_elo(SEQ, "2010-01-30"))
EloRating documentation built on March 26, 2020, 7:29 p.m.
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Description Usage Arguments Value Author(s) Examples
Description
standardize Elo ratings between 0 and 1
Usage
1 | scale_elo(x)
|
Arguments
x |
numeric, a vector of Elo ratings |
Value
a numeric vector of Elo ratings, which are scaled between 0 and 1, with the highest rating that is supplied becoming 1, the lowest becoming 0, and all others being proportionally scaled in between
Author(s)
Christof Neumann
Examples
1 2 3 4 5 6 7 | data(adv)
SEQ <- elo.seq(winner=adv$winner, loser=adv$loser, Date=adv$Date)
extract_elo(SEQ, "2010-01-30")
extract_elo(SEQ, "2010-01-30", standardize=TRUE)
# same as
scale_elo(extract_elo(SEQ, "2010-01-30"))
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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