summary.dreamer_mcmc {dreamer} | R Documentation |
Summarize Model Output
Description
Produces summaries for inference and diagnosing MCMC chains.
Usage
## S3 method for class 'dreamer_mcmc'
summary(object, ...)
Arguments
object |
MCMC output from a dreamer model. |
... |
additional arguments which are ignored. |
Value
A tibble with inference and diagnostics information for each parameter.
Examples
set.seed(888)
data <- dreamer_data_linear(
n_cohorts = c(20, 20, 20),
dose = c(0, 3, 10),
b1 = 1,
b2 = 3,
sigma = 5
)
# Bayesian model averaging
output <- dreamer_mcmc(
data = data,
n_adapt = 1e3,
n_burn = 1e3,
n_iter = 1e4,
n_chains = 2,
silent = FALSE,
mod_linear = model_linear(
mu_b1 = 0,
sigma_b1 = 1,
mu_b2 = 0,
sigma_b2 = 1,
shape = 1,
rate = .001,
w_prior = 1 / 2
),
mod_quad = model_quad(
mu_b1 = 0,
sigma_b1 = 1,
mu_b2 = 0,
sigma_b2 = 1,
mu_b3 = 0,
sigma_b3 = 1,
shape = 1,
rate = .001,
w_prior = 1 / 2
)
)
# all models (also show model weights)
summary(output)
# single model
summary(output$mod_linear)
[Package dreamer version 3.1.0 Index]