# Fits the Bradley-Terry Model to Potentially Large and Sparse Networks of Comparison Data

## Documentation for package ‘BradleyTerryScalable’ version 0.1.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

BradleyTerryScalable-package | A package for fitting the Bradley-Terry model to (potentially) large and sparse data sets.
BradleyTerryScalable | A package for fitting the Bradley-Terry model to (potentially) large and sparse data sets.
btdata | Create a btdata object
btfit | Fits the Bradley-Terry model
btprob | Calculates Bradley-Terry probabilities
BT_EM | Fit the Bradley-Terry model using the EM or MM algorithm
citations | Statistics Journal Citation Data from Stigler (1994)
codes_to_counts | Converts data frame with a code for wins to counts of wins
coef.btfit | Extract coefficients of a 'btfit' object
fitted.btfit | Fitted Method for "btfit"
select_components | Subset a btdata object
simulate.btfit | This function simulates one or more pseudo-random datasets from a specified Bradley-Terry model. Counts are simulated from independent binomial distributions, with the binomial probabilities and totals specified through the function arguments.
simulate_BT | This function simulates one or more pseudo-random datasets from a specified Bradley-Terry model. Counts are simulated from independent binomial distributions, with the binomial probabilities and totals specified through the function arguments.
summary.btdata | Create a btdata object
summary.btfit | Summarizing Bradley-Terry Fits
toy_data | A toy data set for the 'BradleyTerryScalable' package
vcov.btfit | Calculate variance-covariance matrix for a btfit object