run_mcmc: Run the BTUN MCMC algorithm

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

Description

This function runs the BTUN mcmc algorithm

Usage

run_mcmc(n.iter, delta, k.mean, k.chol, win.matrix, f.initial, alpha = FALSE)

Arguments

n.iter	The number of iterations to be run
delta	The underrlaxed tuning parameter must be in (0, 1)
k.mean	The GP prior mean vector
k.chol	The cholesky decomposition of the GP prior covariance matrix
win.matrix	A matrix, where w_ij give the number of times area i beat j
f.initial	A vector of the intial esitmate for f
alpha	A boolean if inference for alpha should be carried out

Value

A list of MCMC output

• f.matrix - A matrix containing the each iteration of f

• alpha.sq - A vector containing the iterations of alpha^2

• accpetance.rate - The acceptance rate for f

• time.taken - Time tkane to run the MCMC algorithm in seconds

Examples

n.iter <- 10
delta <- 0.1
k.mean <- c(0, 0, 0)
k.chol <- diag(3)
comparisons <- data.frame("winner" = c(1, 3, 2, 2), "loser" = c(3, 1, 1, 3))
win.matrix <- comparisons_to_matrix(3, comparisons)
f.initial <- c(0, 0, 0)

mcmc.output <- run_mcmc(n.iter, delta, k.mean, k.chol, win.matrix, f.initial)

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