Plots and calculates many summary statistics from the infection history MCMC chain
plot_posteriors_infhist( inf_chain, years, n_alive, known_ar = NULL, known_infection_history = NULL, burnin = 0, samples = 100, pad_chain = TRUE )
| inf_chain | the data table with infection history samples from |
|---|---|
| years | vector of the epochs of potential circulation |
| known_ar | data frame of known attack rates, if known. |
| known_infection_history | data frame of known infection histories. |
| burnin | if not already discarded, discard burn in from chain (takes rows where samp_no > burnin) |
| samples | how many samples from the chain to take |
| pad_chain | if TRUE, pads the infection history MCMC chain with non-infection events |
| n_alive_group | vector with the number of people alive in each year of circulation. |
a list of ggplot objects and data frame of posterior estimates
Other infection_history_plots:
calculate_infection_history_statistics(),
generate_cumulative_inf_plots(),
plot_data(),
plot_infection_histories(),
plot_infection_history_chains_indiv(),
plot_infection_history_chains_time(),
plot_number_infections(),
plot_total_number_infections()
if (FALSE) { ## Load in exaple data data(example_inf_chain) data(example_antigenic_map) data(example_titre_dat) strain_isolation_times <- example_antigenic_map$inf_times ## Setup known attack rates n_alive <- get_n_alive(example_titre_dat, strain_isolation_times) n_infs <- colSums(example_inf_hist) known_ar <- n_infs/n_alive known_ar <- data.frame("j"=strain_isolation_times,"AR"=known_ar,"group"=1) ## Setup known infection histories known_inf_hist <- data.frame(example_inf_hist) colnames(known_inf_hist) <- strain_isolation_times n_alive_group <- get_n_alive_group(example_titre_dat, strain_isolation_times,melt_dat = TRUE) n_alive_group$j <- strain_isolation_times[n_alive_group$j] all_plots <- plot_posteriors_infhist(example_inf_chain, strain_isolation_times, n_alive_group, known_ar=known_ar,known_infection_history = known_inf_hist, samples=100) }