Plot Prior

Plot the prior over the dose range. This is intended to help the user choose appropriate priors.

dreamer_plot_prior(
  n_samples = 10000,
  probs = c(0.025, 0.975),
  doses,
  n_chains = 1,
  ...,
  times = NULL,
  plot_draws = FALSE,
  alpha = 0.2
)

Arguments

n_samples

the number of MCMC samples per MCMC chain used to generate the plot.

probs

A vector of length 2 indicating the lower and upper percentiles to plot. Not applicable when plot_draws = TRUE.

doses

a vector of doses at which to evaluate and interpolate between.

n_chains

the number of MCMC chains.

...

model objects. See model and examples below.

times

a vector of times at which to plot the prior.

plot_draws

if TRUE, the individual draws from the prior are plotted. If FALSE, only the prior mean and quantiles are drawn.

alpha

the transparency setting for the prior draws in (0, 1]. Only applies if plot_draws = TRUE.

Value

The ggplot object.

Examples

# Plot prior for one model
set.seed(8111)
dreamer_plot_prior(
 doses = c(0, 2.5, 5),
 mod_quad_binary = model_quad_binary(
   mu_b1 = -.5,
   sigma_b1 = .2,
   mu_b2 = -.5,
   sigma_b2 = .2,
   mu_b3 = .5,
   sigma_b3 = .1,
   link = "logit",
   w_prior = 1
 )
)


# plot individual draws
dreamer_plot_prior(
 doses = seq(from = 0, to = 5, length.out = 50),
 n_samples = 100,
 plot_draws = TRUE,
 mod_quad_binary = model_quad_binary(
   mu_b1 = -.5,
   sigma_b1 = .2,
   mu_b2 = -.5,
   sigma_b2 = .2,
   mu_b3 = .5,
   sigma_b3 = .1,
   link = "logit",
   w_prior = 1
 )
)


# plot prior from mixture of models
dreamer_plot_prior(
 doses = c(0, 2.5, 5),
 mod_linear_binary = model_linear_binary(
   mu_b1 = -1,
   sigma_b1 = .1,
   mu_b2 = 1,
   sigma_b2 = .1,
   link = "logit",
   w_prior = .75
 ),
 mod_quad_binary = model_quad_binary(
   mu_b1 = -.5,
   sigma_b1 = .2,
   mu_b2 = -.5,
   sigma_b2 = .2,
   mu_b3 = .5,
   sigma_b3 = .1,
   link = "logit",
   w_prior = .25
 )
)