Nothing
## ---- setup, echo = F---------------------------------------------------------
knitr::opts_chunk$set(fig.width = 6, fig.height = 6, eval = FALSE, echo = TRUE)
## ---- echo = F----------------------------------------------------------------
# set.seed(2020)
## -----------------------------------------------------------------------------
# library("devtools")
# devtools::install_github("rvpanaro/bsem", dependencies = TRUE)
## -----------------------------------------------------------------------------
# install.packages("bsem", dependencies = TRUE)
## -----------------------------------------------------------------------------
# sem(
# data,
# blocks,
# paths,
# exogenous,
# signals,
# row_names = rownames(data),
# prior_specs = list(
# beta = c("normal(0,1)"),
# sigma2 = c("inv_gamma(2.1, 1.1)"),
# gamma0 = c("normal(0,1)"), gamma = c("normal(0,1)"),
# tau2 = c("inv_gamma(2.1, 1.1)")
# ),
# cores = parallel::detectCores(),
# pars = c("alpha", "lambda", "sigma2"),
# iter = 2000,
# chains = 4,
# scaled = FALSE,
# ...
# )
## ---- eval = TRUE-------------------------------------------------------------
dt <- bsem::simdata()
names(dt)
## ---- eval = TRUE-------------------------------------------------------------
dt$exogenous
## ---- eval = TRUE-------------------------------------------------------------
dt$blocks
## ---- eval = TRUE-------------------------------------------------------------
colnames(dt$data)
## -----------------------------------------------------------------------------
# fit <- bsem::sem(
# data = dt$data,
# blocks = dt$blocks,
# paths = dt$paths,
# exogenous = dt$exogenous,
# signals = dt$signals
# )
#
# fit
## -----------------------------------------------------------------------------
# plot(fit)
## -----------------------------------------------------------------------------
# gridExtra::grid.arrange(
# bsem::arrayplot(fit$mean_lambda, main = "estimates"),
# bsem::arrayplot(dt$real$lambda, main = "lambda (scores)")
# )
#
# gridExtra::grid.arrange(
# bsem::arrayplot(fit$mean_alpha, main = "estimates"),
# bsem::arrayplot(dt$real$alpha, main = "alpha (loadings)"),
# layout_matrix = matrix(c(1,1,2,2), ncol = 2)
# )
## -----------------------------------------------------------------------------
# summary(fit)
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