The generate.rank.matrix() function requires the user to specify the number of objects (items), called p, and the number of assessors, called n. The function simulates full ranked lists (i.e. no missing assignments) without ties.
Usage
generate.rank.matrix(p, n, percentageMissing = 0)
Value
A list with simulated data
R.input - The rank matrix
thea.true - The true underlying signals from the assessments
sigmas - The standard error of the noise added for each assessor
matrixNoise - The noise added to the true signals in order to get the final rank matrix
Arguments
p
The number of objects.
n
The number of assessors.
percentageMissing
The percentage of the missing values. Note, missing data should be resolved by the rank() function before calling estimateTheta().