ci_mb.RdThis function calculates confidence intervals for parameters in a Mallows-Binomial model using the nonparametric bootstrap.
ci_mb(
rankings,
ratings,
M,
interval = 0.9,
nsamples = 50,
all = FALSE,
method = "ASTAR"
)A matrix of rankings, potentially with attribute "assignments" to signify separate reviewer assignments. One ranking per row.
A matrix of ratings, one row per judge and one column per object.
Numeric specifying maximum (=worst quality) integer rating.
A numeric entry between 0 and 1 specifying the confidence interval (e.g., .90 indicates a 90% confidence interval). Defaults to 0.90.
A numeric entry indicating desired number of bootstrap samples to be used when calculating confidence intervals. Defaults to 50.
A boolean indicating if estimated parameters from all bootstrap samples should be returned.
Defaults to FALSE.
A character string indicating which estimation method to use when estimating parameters. Allowable options are currently "ASTAR", "Greedy", "GreedyLocal", and "FV". Defaults to exact search, "ASTAR".
A list with elements ci, a matrix of confidence intervals for Mallows-Binomial parameters,
ci_ranks, a matrix of confidence intervals for object ranks, bootstrap_pi0, a matrix of
bootstrap consensus rankings (returned only if all==TRUE), and bootstrap_ptheta, a
matrix of bootstrap estimates of (p,theta) (returned only if all==TRUE).
data("ToyData1")
ci_mb(ToyData1$rankings,ToyData1$ratings,ToyData1$M,method="ASTAR",all=TRUE)
#> $ci
#> p1 p2 p3 theta
#> 5% 0.0625000 0.0625000 0.75 1e+08
#> 95% 0.1648437 0.1648437 0.75 1e+08
#>
#> $ci_ranks
#> Object1 Object2 Object3
#> 5% 1 2 3
#> 95% 1 2 3
#>
#> $bootstrap_pi0
#> [,1] [,2] [,3]
#> [1,] 1 2 3
#> [2,] 1 2 3
#> [3,] 1 2 3
#> [4,] 1 2 3
#> [5,] 1 2 3
#> [6,] 1 2 3
#> [7,] 1 2 3
#> [8,] 1 2 3
#> [9,] 1 2 3
#> [10,] 1 2 3
#> [11,] 1 2 3
#> [12,] 1 2 3
#> [13,] 1 2 3
#> [14,] 1 2 3
#> [15,] 1 2 3
#> [16,] 1 2 3
#> [17,] 1 2 3
#> [18,] 1 2 3
#> [19,] 1 2 3
#> [20,] 1 2 3
#> [21,] 1 2 3
#> [22,] 1 2 3
#> [23,] 1 2 3
#> [24,] 1 2 3
#> [25,] 1 2 3
#> [26,] 1 2 3
#> [27,] 1 2 3
#> [28,] 1 2 3
#> [29,] 1 2 3
#> [30,] 1 2 3
#> [31,] 1 2 3
#> [32,] 1 2 3
#> [33,] 1 2 3
#> [34,] 1 2 3
#> [35,] 1 2 3
#> [36,] 1 2 3
#> [37,] 1 2 3
#> [38,] 1 2 3
#> [39,] 1 2 3
#> [40,] 1 2 3
#> [41,] 1 2 3
#> [42,] 1 2 3
#> [43,] 1 2 3
#> [44,] 1 2 3
#> [45,] 1 2 3
#> [46,] 1 2 3
#> [47,] 1 2 3
#> [48,] 1 2 3
#> [49,] 1 2 3
#> [50,] 1 2 3
#>
#> $bootstrap_ptheta
#> p1 p2 p3 theta
#> [1,] 0.125000 0.125000 0.75 1e+08
#> [2,] 0.156250 0.156250 0.75 1e+08
#> [3,] 0.125000 0.125000 0.75 1e+08
#> [4,] 0.062500 0.062500 0.75 1e+08
#> [5,] 0.125000 0.125000 0.75 1e+08
#> [6,] 0.062500 0.062500 0.75 1e+08
#> [7,] 0.125000 0.125000 0.75 1e+08
#> [8,] 0.062500 0.062500 0.75 1e+08
#> [9,] 0.125000 0.125000 0.75 1e+08
#> [10,] 0.109375 0.109375 0.75 1e+08
#> [11,] 0.093750 0.093750 0.75 1e+08
#> [12,] 0.109375 0.109375 0.75 1e+08
#> [13,] 0.078125 0.078125 0.75 1e+08
#> [14,] 0.156250 0.156250 0.75 1e+08
#> [15,] 0.140625 0.140625 0.75 1e+08
#> [16,] 0.109375 0.109375 0.75 1e+08
#> [17,] 0.156250 0.156250 0.75 1e+08
#> [18,] 0.203125 0.203125 0.75 1e+08
#> [19,] 0.062500 0.062500 0.75 1e+08
#> [20,] 0.140625 0.140625 0.75 1e+08
#> [21,] 0.125000 0.125000 0.75 1e+08
#> [22,] 0.140625 0.140625 0.75 1e+08
#> [23,] 0.109375 0.109375 0.75 1e+08
#> [24,] 0.125000 0.125000 0.75 1e+08
#> [25,] 0.125000 0.125000 0.75 1e+08
#> [26,] 0.125000 0.125000 0.75 1e+08
#> [27,] 0.140625 0.140625 0.75 1e+08
#> [28,] 0.171875 0.171875 0.75 1e+08
#> [29,] 0.156250 0.156250 0.75 1e+08
#> [30,] 0.140625 0.140625 0.75 1e+08
#> [31,] 0.125000 0.125000 0.75 1e+08
#> [32,] 0.093750 0.093750 0.75 1e+08
#> [33,] 0.187500 0.187500 0.75 1e+08
#> [34,] 0.140625 0.140625 0.75 1e+08
#> [35,] 0.140625 0.140625 0.75 1e+08
#> [36,] 0.125000 0.125000 0.75 1e+08
#> [37,] 0.125000 0.125000 0.75 1e+08
#> [38,] 0.125000 0.125000 0.75 1e+08
#> [39,] 0.156250 0.156250 0.75 1e+08
#> [40,] 0.109375 0.109375 0.75 1e+08
#> [41,] 0.125000 0.125000 0.75 1e+08
#> [42,] 0.140625 0.140625 0.75 1e+08
#> [43,] 0.093750 0.093750 0.75 1e+08
#> [44,] 0.109375 0.109375 0.75 1e+08
#> [45,] 0.062500 0.062500 0.75 1e+08
#> [46,] 0.140625 0.140625 0.75 1e+08
#> [47,] 0.140625 0.140625 0.75 1e+08
#> [48,] 0.062500 0.062500 0.75 1e+08
#> [49,] 0.093750 0.093750 0.75 1e+08
#> [50,] 0.109375 0.109375 0.75 1e+08
#>