Function reference • rankrate

Density, Random Data Generation, and Helper Functions Functions that allow for calculating the density of rankings and ratings, random sampling of Mallows and Mallows-Binomial random variables, and associated helper functions.
`dmall()`	Calculate the density of rankings under a Mallows distribution
`dmb()`	Calculate the density of rankings and ratings under a Mallows-Binomial distribution.
`rmall()`	Random Mallows generation.
`rmb()`	Random Mallows-Binomial generation
`psi()`	Normalizing constant function of a Mallows distribution, psi
`kendall()`	Calculate the Kendall's tau between rankings
`to_rankings()`	Convert ranks into rankings (orderings)
`getQ()`	Calculate Q Matrix
Model Estimation Functions Functions that allow for estimation of Mallows-Binomial models and uncertainty quantification via the nonparametric bootstrap.
`fit_mb()`	Calculate the exact or approximate MLE of a Mallows-Binomial distribution using various methods
`ci_mb()`	Bootstrap Confidence Intervals for Mallows-Binomial parameters.
`ASTAR()`	Calculate the exact MLE of a Mallows-Binomial distribution using an A* algorithm
`FV()`	Estimate the MLE of a Mallows-Binomial distribution using the FV method
`Greedy()`	Estimate the MLE of a Mallows-Binomial distribution using the Greedy method
`GreedyLocal()`	Estimate the MLE of a Mallows-Binomial distribution using the "Greedy Local" method
Built-In Datasets Four data sets of rankings and ratings to demonstrate model capabilities and key functions.
`AIBS`	Real peer review data set from the American Institute of Biological Sciences (AIBS)
`ToyData1`	Toy data set of rankings and ratings demonstrating tie-breaking
`ToyData2`	Toy data set of rankings and ratings demonstrating decision-making with partial rankings
`ToyData3`	Toy data set of rankings and ratings when judges express internally inconsistent preferences

Reference

Density, Random Data Generation, and Helper Functions

Model Estimation Functions

Built-In Datasets