`R/bpc_rank_of_players.R`

`get_rank_of_players_df.Rd`

To print this object you should remove the last column PosteriorRank since it contain the whole posterior distribution for each case

get_rank_of_players_df(bpc_object, n = 1000)

bpc_object | a bpc object |
---|---|

n | Number of times we will sample the posterior |

a data frame. This data frame contains the median of the rank, the mean, the standard deviation of the rank

# \donttest{ m<-bpc(data = tennis_agresti, player0 = 'player0', player1 = 'player1', result_column = 'y', model_type = 'bt', solve_ties = 'none') #> Running MCMC with 4 parallel chains... #> #> Chain 1 finished in 3.8 seconds. #> Chain 2 finished in 3.9 seconds. #> Chain 3 finished in 3.8 seconds. #> Chain 4 finished in 3.8 seconds. #> #> All 4 chains finished successfully. #> Mean chain execution time: 3.8 seconds. #> Total execution time: 4.0 seconds. rank_m<-get_rank_of_players_df(m,n=100) print(rank_m) #> Parameter MedianRank MeanRank StdRank #> 1 Graf 1 1.46 0.6422813 #> 2 Seles 2 2.00 0.9211324 #> 3 Navratilova 3 2.96 0.8518548 #> 4 Sabatini 4 3.82 0.7962031 #> 5 Sanchez 5 4.76 0.5148306 # }