Closed osorensen closed 6 months ago
Here is "proof" that it reproduces Metropolis-Hastings output. Note that we need quite a lot of MCMC steps.
library(BayesMallows) library(patchwork) set.seed(1) dat <- subset(beach_preferences, assessor < 5) mod_init <- compute_mallows( data = setup_rank_data(preferences = dat), compute_options = set_compute_options(nmc = 10000, burnin = 1000) ) alpha <- numeric() mod <- mod_init for(i in 6:60) { print(i) mod <- update_mallows( model = mod, new_data = setup_rank_data(preferences = subset(beach_preferences, assessor == i), timepoint = i), smc_options = set_smc_options( n_particles = 10000, mcmc_steps = 200) ) alpha <- c(alpha, mean(mod$alpha_samples)) } #> [1] 6 #> [1] 7 #> [1] 8 #> [1] 9 #> [1] 10 #> [1] 11 #> [1] 12 #> [1] 13 #> [1] 14 #> [1] 15 #> [1] 16 #> [1] 17 #> [1] 18 #> [1] 19 #> [1] 20 #> [1] 21 #> [1] 22 #> [1] 23 #> [1] 24 #> [1] 25 #> [1] 26 #> [1] 27 #> [1] 28 #> [1] 29 #> [1] 30 #> [1] 31 #> [1] 32 #> [1] 33 #> [1] 34 #> [1] 35 #> [1] 36 #> [1] 37 #> [1] 38 #> [1] 39 #> [1] 40 #> [1] 41 #> [1] 42 #> [1] 43 #> [1] 44 #> [1] 45 #> [1] 46 #> [1] 47 #> [1] 48 #> [1] 49 #> [1] 50 #> [1] 51 #> [1] 52 #> [1] 53 #> [1] 54 #> [1] 55 #> [1] 56 #> [1] 57 #> [1] 58 #> [1] 59 #> [1] 60 mod_bmm <- compute_mallows( data = setup_rank_data(preferences = beach_preferences), compute_options = set_compute_options(nmc = 50000, burnin = 1000) ) plot(mod_bmm) + plot(mod) + plot_layout(ncol = 1)
Created on 2024-03-06 with reprex v2.1.0
Here is "proof" that it reproduces Metropolis-Hastings output. Note that we need quite a lot of MCMC steps.
Created on 2024-03-06 with reprex v2.1.0