dreamer_plot_prior | R Documentation |
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 )
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 |
doses |
a vector of doses at which to evaluate and interpolate between. |
n_chains |
the number of MCMC chains. |
... |
model objects. See |
times |
a vector of times at which to plot the prior. |
plot_draws |
if |
alpha |
the transparency setting for the prior draws in (0, 1].
Only applies if |
The ggplot object.
# 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 ) )
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.