Fit beta distribution to MCMC output

Source: R/priors.R

Attempts to fit a beta distribution to a data frame of MCMC output from a previous run.

fit_beta_prior(
  chain_samples,
  par_name = "",
  error_tol = 999999999,
  try_attempts = 10,
  plot_fit = TRUE
)

Arguments

chain_samples

the MCMC chain data frame to be fit to
par_name

the column label to fit to
error_tol

= 9999999999999, what's the error tolerance on the fit? Might take some tweaking
try_attempts

= 10 how many fitting attempts to try before giving up
plot_fit

= TRUE, if TRUE, plots the fit to the MCMC chain

Value

the model fit object as returned by optim

See also

fit_normal_prior

Other priors: calc_phi_probs_indiv(), calc_phi_probs_spline(), calc_phi_probs(), create_prior_mu(), create_prob_shifts(), find_beta_prior_mode(), find_beta_prior_with_mean_var(), find_beta_prior_with_mean(), fit_normal_prior(), inf_mat_prior(), infection_history_prior(), prob_mus(), prob_shifts()

Examples

if (FALSE) {
## Output from a previous serosolver chain
chain <- read.csv("madeup_chain.csv")
results <- fit_beta_prior(chain, par_name="sigma1",plot_fit=FALSE)
}