## ----opts, echo = FALSE, message = FALSE, warning = FALSE---------------------
knitr::opts_chunk$set(collapse = TRUE, comment = " ", fig.width = 7, fig.height = 7, fig.align = "center")

## ----eval = FALSE-------------------------------------------------------------
# install.packages("BDgraph")
# 
# library(BDgraph)

## ----pressure, echo = FALSE, out.width = '85%'--------------------------------
knitr::include_graphics("Figure_1.png")

## ----eval = FALSE-------------------------------------------------------------
# bdgraph(data, n = NULL, method = "ggm", algorithm = "bdmcmc", iter = 5000,
#         burnin = iter / 2, not.cont = NULL, g.prior = 0.5, df.prior = 3,
#         g.start = "empty", jump = NULL, save = FALSE,
#         cores = NULL, threshold = 1e-8, verbose = TRUE)

## ----eval = FALSE-------------------------------------------------------------
# plinks(bdgraph.obj, round = 2, burnin = NULL)

## ----eval = FALSE-------------------------------------------------------------
# select(bdgraph.obj, cut = NULL, vis = FALSE)

## ----eval = FALSE-------------------------------------------------------------
# plotcoda(bdgraph.obj, thin = NULL, control = TRUE, main = NULL,
#          verbose = TRUE, ...)

## ----eval = FALSE-------------------------------------------------------------
# traceplot(bdgraph.obj, acf = FALSE, pacf = FALSE, main = NULL, ...)

## ----eval = FALSE-------------------------------------------------------------
# compare(pred, actual, main = NULL, vis = FALSE)

## ----eval = FALSE-------------------------------------------------------------
# plotroc = function(pred, actual, cut = 20, smooth = FALSE, ...)

## ----eval = FALSE-------------------------------------------------------------
# bdgraph.sim(p = 10, graph = "random", n = 0, type = "Gaussian", prob = 0.2,
#             size = NULL, mean = 0, class = NULL, cut = 4, b = 3,
#             D = diag(p), K = NULL, sigma = NULL,
#             q = exp(-1), beta = 1, vis = FALSE, rewire = 0.05,
#             range.mu = c(3, 5), range.dispersion = c(0.01, 0.1))

## ----eval = FALSE-------------------------------------------------------------
# graph.sim(p = 10, graph = "random", prob = 0.2, size = NULL, class = NULL,
#           vis = FALSE, rewire = 0.05)

## -----------------------------------------------------------------------------
library(BDgraph)

set.seed(5)

data.sim <- bdgraph.sim(n = 60, p = 8, graph = "scale-free", type = "Gaussian")
round(head(data.sim $ data, 4), 2) 

## ----eval = TRUE--------------------------------------------------------------
sample.bdmcmc <- bdgraph(data = data.sim, method = "ggm", algorithm = "bdmcmc", 
                         iter = 5000, save = TRUE, verbose = FALSE)

## -----------------------------------------------------------------------------
summary(sample.bdmcmc)

## -----------------------------------------------------------------------------
sample.rjmcmc <- bdgraph(data = data.sim, method = "ggm", algorithm = "rjmcmc", 
                         iter = 5000, save = TRUE, verbose = FALSE)

## ----eval = FALSE-------------------------------------------------------------
# plotroc(list(sample.bdmcmc, sample.rjmcmc), data.sim, smooth = TRUE,
#          labels = c("BDMCMC", "RJMCMC"), color = c("blue", "red"))

## -----------------------------------------------------------------------------
compare(list(sample.bdmcmc, sample.rjmcmc), data.sim, 
        main = c("True graph", "BDMCMC", "RJMCMC"), vis = TRUE)

## -----------------------------------------------------------------------------
plotcoda(sample.bdmcmc, verbose = FALSE)
plotcoda(sample.rjmcmc, verbose = FALSE)