inst/doc/MCMCsettings.R

In JointAI: Joint Analysis and Imputation of Incomplete Data

## ----setup, include = FALSE-----------------------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 7,
  fig.align = 'center'
  # fig.path = "figures_MCMCsettings/"
)
library(JointAI)
options(width = 100)

## ----message = FALSE------------------------------------------------------------------------------
mod1 <- lm_imp(SBP ~ alc, data = NHANES, n.iter = 100, progress.bar = 'none')

## ----echo = FALSE---------------------------------------------------------------------------------
a1 <- capture.output(print(summary(mod1)))
cat(paste0('[...]', '\n', paste(a1[18:22], collapse = "\n")))

## ----message = FALSE------------------------------------------------------------------------------
mod2 <- lm_imp(
  SBP ~ alc,
  data = NHANES,
  n.adapt = 10,
  n.iter = 100,
  progress.bar = 'none'
)

## ----echo = FALSE---------------------------------------------------------------------------------
a2 <- capture.output(print(summary(mod2)))
cat(paste0('[...]', '\n', paste(a2[19:23], collapse = "\n")))

## ----message = FALSE------------------------------------------------------------------------------
mod3 <- lm_imp(
  SBP ~ alc,
  data = NHANES,
  n.iter = 500,
  thin = 10,
  progress.bar = 'none'
)

## ----echo = FALSE---------------------------------------------------------------------------------
a3 <- capture.output(print(summary(mod3)))
cat(paste0('[...]', '\n', paste(a3[19:23], collapse = "\n")))

## ----message = FALSE------------------------------------------------------------------------------
init_list <- lapply(1:3, function(i) {
  list(beta = rnorm(4), tau_SBP = rgamma(1, 1, 1))
})

init_list

## ----message = FALSE------------------------------------------------------------------------------
mod4a <- lm_imp(
  SBP ~ gender + age + WC,
  data = NHANES,
  progress.bar = 'none',
  inits = init_list
)

mod4a$mcmc_settings$inits

## ----message = FALSE------------------------------------------------------------------------------
inits_fun <- function() {
  list(beta = rnorm(4), alpha = rnorm(3))
}

inits_fun()


mod4b <- lm_imp(
  SBP ~ gender + age + WC,
  data = NHANES,
  progress.bar = 'none',
  inits = inits_fun
)

mod4b$mcmc_settings$inits

## ----message = FALSE, warning = FALSE-------------------------------------------------------------
mod4c <- lme_imp(
  bmi ~ time + HEIGHT_M + hc + SMOKE,
  random = ~ time | ID,
  data = simLong,
  no_model = 'time',
  progress.bar = 'none'
)

str(coef(mod4c$model))

## ----echo = FALSE, message = FALSE, warning = FALSE-----------------------------------------------
mod4c <- lme_imp(
  bmi ~ time + HEIGHT_M + hc + SMOKE,
  random = ~ time | ID,
  data = simLong,
  no_model = 'time',
  progress.bar = 'none'
)

options(max.print = 1e5)
a4 <- capture.output(coef(mod4c$model))
a4mod <- capture.output(mod4c$jagsmodel)

## ----eval = FALSE---------------------------------------------------------------------------------
# head(mod4c$data_list$M_ID, 8)

## ----echo = FALSE---------------------------------------------------------------------------------
mat <- mod4c$data_list$M_ID[1:8, ]
colnames(mat) <- gsub(
  "SMOKEsmoked until pregnancy was known",
  "SMOKEsmoked until[...]",
  gsub("SMOKEcontinued smoking in pregnancy", "SMOKEcontin[...]", colnames(mat))
)
mat

## -------------------------------------------------------------------------------------------------
head(coef(mod4c$model)$M_ID, 8)

## ----echo = FALSE---------------------------------------------------------------------------------
cat(paste0(
  '[...]\n',
  paste0(a4mod[58:60], collapse = "\n"),
  '\n\n[...]\n',
  paste0(a4mod[69:72], collapse = "\n"),
  '\n\n[...]'
))

## -------------------------------------------------------------------------------------------------
mod4c$data_list['RinvD_bmi_ID']

## ----echo = FALSE---------------------------------------------------------------------------------
cat(paste0('[...]\n', paste(a4mod[25:31], collapse = '\n'), '\n[...]\n'))

## -------------------------------------------------------------------------------------------------
coef(mod4c$model)$RinvD_bmi_ID

## ----eval = FALSE---------------------------------------------------------------------------------
# future::plan(future::multisession, workers = 4)

## ----eval = FALSE---------------------------------------------------------------------------------
# future::plan(future::sequential())