nb_bart: Notebook generator: BART

In ooelrich/oscbvar: Stuff for Bayesian vector autoregressions

Description

Generates a notebook for a BART model.

Usage

nb_bart(
  data = oscbvar::macrodata[, 1:7],
  agc = list(5, 60, TRUE, 1),
  lags = 1,
  include_intercept = FALSE,
  nrep = 10000,
  nburn = 5000
)

Arguments

data	Dataset from which to generate the notebook. Defaults to the macroeconomic data set from this package using all variables.
agc	List of atomic prediction generation controllers. The first element of the list gives the starting time (ie what observation is considered as t = 1), the second element is the minimum window length used for estimation, and the third one is a boolean indicating if the estimation window is rolling or not, the forth indicates which variable is the response variable and it defaults to 1 (GDP).
lags	The order of the VAR. Defaults to 1.
include_intercept	Whether to include an intercep in the design matrix or not. Defaults to FALSE since the intercept breaks the function.
nrep	Number of MCMC draws (after burn-in)
nburn	Number of burn-in draws

Details

Uses default settings in dbarts.

ooelrich/oscbvar documentation built on Sept. 8, 2021, 3:31 p.m.