plot.bvar_fcast {BVAR}  R Documentation 
Plotting method for forecasts obtained from predict.bvar
.
Forecasts of all or a subset of the available variables can be plotted.
## S3 method for class 'bvar_fcast' plot( x, vars = NULL, col = "#737373", t_back = 1, area = FALSE, fill = "#808080", variables = NULL, orientation = c("vertical", "horizontal"), mar = c(2, 2, 2, 0.5), ... )
x 
A 
vars 
Optional numeric or character vector. Used to subset the plot to
certain variables by position or name (must be available). Defaults to

col 
Character vector. Colour(s) of the lines delineating credible
intervals. Single values will be recycled if necessary. Recycled HEX color
codes are varied in transparency if not provided (e.g. "#737373FF"). Lines
can be bypassed by setting this to 
t_back 
Integer scalar. Number of observed datapoints to plot ahead of the forecast. 
area 
Logical scalar. Whether to fill the credible intervals using

fill 
Character vector. Colour(s) to fill the credible intervals with. See col for more information. 
variables 
Optional character vector. Names of all variables in the
object. Used to subset and title. Taken from 
orientation 
String indicating the orientation of the plots. Defaults
to 
mar 
Numeric vector. Margins for 
... 
Other graphical parameters for 
Returns x invisibly.
# 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) # Store predictions expost predict(x) < predict(x) # Plot forecasts for all available variables plot(predict(x)) # Subset to variables in positions 1 and 3 via their name plot(predict(x), vars = c("CPI", "FED")) # Subset via position, increase the plotted forecast horizon and past data plot(predict(x, horizon = 20), vars = c(1, 3), t_back = 10) # Adjust confidence bands and the plot's orientation plot(predict(x, conf_bands = 0.25), orientation = "h") # Draw areas inbetween the confidence bands and skip drawing lines plot(predict(x), col = "transparent", area = TRUE) # Plot a conditional forecast (with a constrained second variable). plot(predict(x, cond_path = c(1, 1, 1, 1, 1, 1), cond_var = 2))