DBL rating algorithm Wrapper arround `dbl` update algorithm. Wrapper allows user to simplify calculation providing only data and initial parameters assumptions
dbl_run(formula, data, r, rd, beta, weight, idlab, kappa = 0.5,
init_r = 0, init_rd = 1, pb = FALSE)formula specifying model. DBL allows multiple variables in formula, also two-way interaction are available specified by `:`. `dbl` formula require first variable to be player name or identifier. LHS needs `rank|id`, to specify competitors order and event `id`.
data.frame which contains columns specified in formula, and optionaly columns defined by `beta`, `weight` or `date`.
named vector of initial estimates. If there is no assumption, initial ratings is set to be r=0.
named vector of initial variance of `r` estimates. In there is no assumption, initial is set to be rd=1.
The additional variance of performance. As beta increases, the performance is more uncertain and update change is smaller. By default `beta = 25/6`.
name of column in `data` containing weights. Weights increasing or decreasing update change. Higher weight increasing impact of corresponding event.
name of column in `data` containing date. Doesn't affect estimation process. If specified, charts displays estimates changes in time in
parameter controlling `rd` to avoid quick decreasing to zero. Is the proportion of `rd` which is maximum change size.
initial values for `r` if not provided. Default `r=0`
initial values for `rd` if not provided. Default `rd=1`
logical, if TRUE progress bar will appear in console. Default = FALSE
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 challange.
class of the object
method type of algorithm used
formula modelled formula
# NOT RUN {
data <- data.frame( name = c( "A", "B", "C", "D" ),
rank = c( 3, 4, 1, 2 ))
dbl <- dbl_run( rank ~ name, data)
# }
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