pairs_predict: Pairwise visualization of out-of-sample posterior predictive...

In bayesianVARs: MCMC Estimation of Bayesian Vectorautoregressions

Pairwise visualization of out-of-sample posterior predictive densities.

Description

Pairwise visualization of out-of-sample posterior predictive densities.

Usage

## S3 method for class 'bayesianVARs_predict'
pairs(x, vars, ahead, ...)

Arguments

x	An object of class bayesianVARs_predict obtained via predict.bayesianVARs_bvar().
vars	Integer vector (or coercible to such) indicating which variables to plot.
ahead	Integer vector (or coercible to such) indicating which step ahead to plot. max(ahead) must be smaller equal to dim(x$predictions)[1].
...	Currently ignored!

Value

Returns x invisibly.

Note

Note that that bayesianVARs_predict can also be used withing plot.bayesianVARs_bvar().

See Also

Other plotting plot.bayesianVARs_bvar(), plot.bayesianVARs_fitted(), plot.bayesianVARs_predict() posterior_heatmap().

Examples

# Access a subset of the usmacro_growth dataset
data <- usmacro_growth[,c("GDPC1", "CPIAUCSL", "FEDFUNDS")]

# Estimate a model
mod <- bvar(data, sv_keep = "all", quiet = TRUE)

# Simulate from posterior predictive
predictions <- predict(mod, ahead = 1:3)

# Visualize
pairs(predictions, vars = 1:3, ahead = 1:3)

bayesianVARs documentation built on April 3, 2025, 6:25 p.m.