inst/doc/dynamite_priors.R

In dynamite: Bayesian Modeling and Causal Inference for Multivariate Longitudinal Data

## -----------------------------------------------------------------------------
#| label: setup
#| echo: false
#| warning: false
library("dynamite")
library("ggplot2")
suppressPackageStartupMessages(library("dplyr"))
theme_set(theme_bw())
options(dplyr.summarise.inform = FALSE)
options(crayon.enabled = FALSE)
set.seed(0)
data.table::setDTthreads(1) # For CRAN
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)


## -----------------------------------------------------------------------------
f <- obs(y ~ -1 + z + varying(~ x + lag(y)) + random(~1 + z), "gaussian") +
  random_spec(correlated = TRUE) + splines(df = 20)
p <- get_priors(f, data = gaussian_example, time = "time", group = "id")
p

## -----------------------------------------------------------------------------
p$prior[p$type == "sigma_nu"] <- "normal(0, 1)" # change prior for sigma_nu
p$prior[p$parameter == "sigma_y"] <- "student_t(3, 0, 2)" # prior for sigma_y
p

## -----------------------------------------------------------------------------
#| eval: false
#| echo: true
# fit <- dynamite(
#   f,
#   data = gaussian_example,
#   time = "time",
#   group = "id",
#   priors = p
# )