bbt_run  R Documentation 
Bayesian BradleyTerry
bbt_run(
formula,
data,
r = numeric(0),
rd = numeric(0),
init_r = 25,
init_rd = 25/3,
lambda = NULL,
share = NULL,
weight = NULL,
kappa = 0.5
)
formula 
formula which specifies the model. RHS Allows only player
rating parameter and it should be specified in following manner:
Users can also specify formula in in different way:

data 
data.frame which contains columns specified in formula, and
optional columns defined by 
r 
named vector of initial players ratings estimates. If not specified
then 
rd 
rd named vector of initial rating deviation estimates. If not specified
then 
init_r 
initial values for 
init_rd 
initial values for 
lambda 
name of the column in 
share 
name of the column in 
weight 
name of the column in 
kappa 
controls 
A "rating" object is returned:
final_r
named vector containing players ratings.
final_rd
named vector containing players ratings deviations.
r
data.frame with evolution of the ratings and ratings deviations
estimated at each event.
pairs
pairwise combinations of players in analysed events with
prior probability and result of a challenge.
class
of the object.
method
type of algorithm used.
settings
arguments specified in function call.
# the simplest example
data < data.frame(
id = c(1, 1, 1, 1),
team = c("A", "A", "B", "B"),
player = c("a", "b", "c", "d"),
rank_team = c(1, 1, 2, 2),
rank_player = c(3, 4, 1, 2)
)
bbt < bbt_run(
data = data,
formula = rank_player  id ~ player(player),
r = setNames(c(25, 23.3, 25.83, 28.33), c("a", "b", "c", "d")),
rd = setNames(c(4.76, 0.71, 2.38, 7.14), c("a", "b", "c", "d"))
)
# nested matchup
bbt < bbt_run(
data = data,
formula = rank_team  id ~ player(player  team)
)
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