tidy.bvar {BVARverse}  R Documentation 
Turn the outputs of a Bayesian VAR (see bvar
) into a
a tidy tibble. Methods are available for bvar
objects (will yield a
subset of coefficient and/or hyperparameter draws), bvar_coefs
objects
(with the coefficients and their quantiles) bvar_fcast
objects (with
predictions, their quantiles and optionally real datapoints), and
bvar_irf
objects (with impulse responses).
## S3 method for class 'bvar' tidy( x, vars = NULL, vars_response = NULL, vars_impulse = NULL, chains = list(), ... ) ## S3 method for class 'bvar_coefs' tidy(x, ...) ## S3 method for class 'bvar_fcast' tidy(x, t_back = 0L, ...) ## S3 method for class 'bvar_irf' tidy(x, ...)
x 
A 
vars 
Character vector used to select variables. Elements are matched
to hyperparameters or coefficients. Coefficients may be matched based on
the dependent variable (by providing the name or position) or the
explanatory variables (by providing the name and the desired lag). See the
example section for a demonstration. Defaults to 
vars_impulse, vars_response 
Optional character or integer vectors used
to select coefficents. Dependent variables are specified with
vars_response, explanatory ones with vars_impulse. Defaults to

chains 
List of 
... 
Not used. 
t_back 
Integer scalar. Whether to include actual datapoints in the tidied forecast. 
Returns a tidy tibble
with relevant
information for further processing.
# Access a subset of the fred_qd dataset data < fred_qd[, c("CPIAUCSL", "UNRATE", "FEDFUNDS")] # Transform it to be stationary data < fred_transform(data, codes = c(5, 5, 1), lag = 4) # Estimate a BVAR using one lag, default settings and very few draws x < bvar(data, lags = 1, n_draw = 1000L, n_burn = 200L, verbose = FALSE) # Create tidy tibbles from the outputs tidy(x) tidy(irf(x)) tidy(predict(x))