params <-
list(EVAL = TRUE)

## ----SETTINGS-knitr, include=FALSE--------------------------------------------
stopifnot(require(knitr))
opts_chunk$set(
  comment=NA,
  eval = if (isTRUE(exists("params"))) params$EVAL else FALSE
)
td <- tempdir()
PATH <- file.path(td, "rstanlm")
if(dir.exists(PATH)) {
  unlink(PATH, recursive = TRUE, force = TRUE)
}

## ----rstan_create_package, eval=FALSE-----------------------------------------
#  library("rstantools")
#  rstan_create_package(path = 'rstanlm')

## ----rstan_create_package-eval, echo=FALSE,warning=FALSE----------------------
library("rstantools")
rstan_create_package(path = PATH, rstudio=FALSE, open=FALSE)

## ----eval=FALSE---------------------------------------------------------------
#  setwd("rstanlm")
#  list.files(all.files = TRUE)

## ----echo=FALSE---------------------------------------------------------------
list.files(PATH, all.files = TRUE)

## ----eval=FALSE---------------------------------------------------------------
#  file.show("DESCRIPTION")

## ----echo=FALSE---------------------------------------------------------------
DES <- readLines(file.path(PATH, "DESCRIPTION"))
cat(DES, sep = "\n")

## ----eval=FALSE---------------------------------------------------------------
#  file.show("Read-and-delete-me")

## ----echo=FALSE---------------------------------------------------------------
cat(readLines(file.path(PATH, "Read-and-delete-me")), sep = "\n")

## ----eval=FALSE---------------------------------------------------------------
#  file.remove('Read-and-delete-me')

## ----echo=FALSE---------------------------------------------------------------
file.remove(file.path(PATH, 'Read-and-delete-me'))

## ----include=FALSE------------------------------------------------------------
stan_prog <- "
data {
  int<lower=1> N;
  vector[N] x;
  vector[N] y;
}
parameters {
  real intercept;
  real beta;
  real<lower=0> sigma;
}
model {
  // ... priors, etc.

  y ~ normal(intercept + beta * x, sigma);
}
"
writeLines(stan_prog, con = file.path(PATH, "inst", "stan", "lm.stan"))
rstan_config(PATH)

## -----------------------------------------------------------------------------
# Save this file as `R/lm_stan.R`

#' Bayesian linear regression with Stan
#'
#' @export
#' @param x Numeric vector of input values.
#' @param y Numeric vector of output values.
#' @param ... Arguments passed to `rstan::sampling` (e.g. iter, chains).
#' @return An object of class `stanfit` returned by `rstan::sampling`
#'
lm_stan <- function(x, y, ...) {
  standata <- list(x = x, y = y, N = length(y))
  out <- rstan::sampling(stanmodels$lm, data = standata, ...)
  return(out)
}


## ----include=FALSE------------------------------------------------------------
Rcode <- "
#' Bayesian linear regression with Stan
#'
#' @export
#' @param x Numeric vector of input values.
#' @param y Numeric vector of output values.
#' @param ... Arguments passed to `rstan::sampling`.
#' @return An object of class `stanfit` returned by `rstan::sampling`
lm_stan <- function(x, y, ...) {
  out <- rstan::sampling(stanmodels$lm, data=list(x=x, y=y, N=length(y)), ...)
  return(out)
}
"
writeLines(Rcode, con = file.path(PATH, "R", "lm_stan.R"))

## ----eval=FALSE---------------------------------------------------------------
#  file.show(file.path("R", "rstanlm-package.R"))

## ----echo=FALSE---------------------------------------------------------------
cat(readLines(file.path(PATH, "R", "rstanlm-package.R")), sep = "\n")

## ----eval = FALSE-------------------------------------------------------------
#  try(roxygen2::roxygenize(load_code = rstantools_load_code), silent = TRUE)
#  roxygen2::roxygenize()

## ----echo=FALSE, results="hide"-----------------------------------------------
try(roxygen2::roxygenize(PATH, load_code = rstantools_load_code), silent = TRUE)
roxygen2::roxygenize(PATH)

## ----eval=FALSE---------------------------------------------------------------
#  # using ../rstanlm because already inside the rstanlm directory
#  install.packages("../rstanlm", repos = NULL, type = "source")

## ----echo=FALSE---------------------------------------------------------------
install.packages(PATH, repos = NULL, type = "source")

## ----eval=FALSE---------------------------------------------------------------
#  library("rstanlm")

## -----------------------------------------------------------------------------
fit <- lm_stan(y = rnorm(10), x = rnorm(10), 
               # arguments passed to sampling
               iter = 2000, refresh = 500)
print(fit)

## ----echo=FALSE---------------------------------------------------------------
unlink(PATH, recursive = TRUE, force = TRUE)