eval_pred_dens: Evaluate the one-step ahead predictive density of a fitted TVP model

Description

eval_pred_dens evaluates the one-step ahead predictive density of a fitted TVP model resulting from a call to shrinkTVP at the points supplied in x. For details on the approximation of the one-step ahead predictive density used, see the vignette.

Usage

eval_pred_dens(x, mod, data_test, log = FALSE)

Value

The value returned is a vector of length length(x), containing the values of the predictive density evaluated at the points supplied in x.

Arguments

x: a real number or a vector of real numbers, taken to be the points at which the predictive density will be evaluated.
mod: an object of class shrinkTVP, containing the fitted model for which the predictive density should be evaluated.
data_test: a data frame with one row, containing the one-step ahead covariates. The names of the covariates have to match the names of the covariates used during model estimation in the call to shrinkTVP.
log: a single logical value determining whether the density should be evaluated on the log scale or not.

Author

Peter Knaus peter.knaus@wu.ac.at

Examples

Run this code

# \donttest{
# Simulate data
set.seed(123)
sim <- simTVP(theta = c(0.2, 0, 0), beta_mean = c(1.5, -0.3, 0))
data <- sim$data

# Estimate model
res <- shrinkTVP(y ~ x1 + x2, data = data[1:199, ])

# Create sequence of x values where the density is to be evaluated
x_vals <- seq(0, 12, by = 0.1)

# Evaluate density and plot
dens <- eval_pred_dens(x_vals, res, data[200, ])
plot(x_vals, dens, type = "l")

# Add vertical line where true value of the one-step ahead y lies
abline(v = data$y[200])
# }