get_probabilities {bpcs} | R Documentation |
Get the empirical win/draw probabilities based on the ability/strength parameters. Instead of calculating from the probability formula given from the model we create a predictive posterior distribution for all pair combinations and calculate the posterior wins/loose/draw The function returns the mean value of win/loose/draw for the player i. To calculate for player j the probability is 1-p_i
get_probabilities(bpc_object, n = 1000)
bpc_object |
a bpc object |
n |
number of samples to draw from the posterior |
a list with data frame table with the respective probabilities and a matrix with the corresponding posterior
m<-bpc(data = tennis_agresti, player0 = 'player0', player1 = 'player1', result_column = 'y', model_type = 'bt', solve_ties = 'none') prob<-get_probabilities(m) print(prob$Table)