BTUN: BTUN: Bradley-Terry for Urban Networks

In jasa-btun-anon/BTUN: BTUN: Bradley--Terry for Urban Networks

Description

The BTUN package allows you to fit a spatial Bradley–Terry model to comparative judgement data sets. The aim is to estimate the deprivation levels in urban areas and find the most deprived citizens. The BTUN model creates a network from the urban area and uses a Gaussian Process to nonparametrically model the deprivation levels.

Covariance Functions

The covariance functions can be used to construct the Gaussian Process prior distribution. There are two functions:

1. registered_adjacency_covariance_function creates a covariance matrix using a network based metric, and

2. registered_covariance_function creates a matrix using the Euclidean distance metric.

MCMC functions

The main MCMC function is run_mcmc, but in cases where the gender of the judges is known the function run_gender_mcmc can be used to analyse how the different genders behave.

jasa-btun-anon/BTUN documentation built on Sept. 12, 2020, 12:54 a.m.