fit_mb.Rd
This function calculates the exact or approximate MLE of a Mallows-Binomial distribution using a user-specified method.
fit_mb(
rankings,
ratings,
M,
method = c("ASTAR", "Greedy", "GreedyLocal", "FV")
)
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 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 pi0
, the estimated consensus ranking MLE, p
, the
estimated object quality parameter MLE, theta
, the estimated scale parameter MLE, and
numnodes
, number of nodes traversed during algorithm and a measure of computational complexity.
If multiple MLEs are found, pi0
, p
, and theta
are returned a matrix elements, with
one row per MLE.
data("ToyData1")
fit_mb(ToyData1$rankings,ToyData1$ratings,ToyData1$M,method="ASTAR")
#> $pi0
#> [1] 1 2 3
#>
#> $p
#> [1] 0.125 0.125 0.750
#>
#> $theta
#> [1] 1e+08
#>
#> $num_nodes
#> [1] 5
#>
fit_mb(ToyData1$rankings,ToyData1$ratings,ToyData1$M,method="Greedy")
#> $pi0
#> [1] 1 2 3
#>
#> $p
#> [1] 0.125 0.125 0.750
#>
#> $theta
#> [1] 1e+08
#>
#> $num_nodes
#> [1] 6
#>
fit_mb(ToyData1$rankings,ToyData1$ratings,ToyData1$M,method="GreedyLocal")
#> $pi0
#> [1] 1 2 3
#>
#> $p
#> [1] 0.125 0.125 0.750
#>
#> $theta
#> [1] 1e+08
#>
#> $num_nodes
#> [1] 9
#>
fit_mb(ToyData1$rankings,ToyData1$ratings,ToyData1$M,method="FV")
#> $pi0
#> [1] 1 2 3
#>
#> $p
#> [1] 0.125 0.125 0.750
#>
#> $theta
#> [1] 1e+08
#>
#> $num_nodes
#> [1] 2
#>