avg_coverage_arima: Compute the average coverage of the prediction intervals...

In helske/tsPI: Improved Prediction Intervals for ARIMA Processes and Structural Time Series

Compute the average coverage of the prediction intervals computed by naive plug-in method and arima_pi

Description

Computes expected coverage probabilities of the prediction intervals of ARMA process by simulating time series from the known model.

Usage

avg_coverage_arima(
  phi = NULL,
  theta = NULL,
  d = 0,
  n,
  n_ahead = 1,
  nsim2,
  nsim = 100,
  level = 0.95,
  prior = "uniform",
  return_all_coverages = FALSE,
  ...
)

Arguments

phi	vector containing the AR parameters
theta	vector containing the MA parameters
d	degree of differencing
n	length of the time series
n_ahead	length of the forecast horizon
nsim2	number of simulations used in computing the expected coverage
nsim	number of simulations used in importance sampling
level	desired coverage probability of the prediction intervals
prior	prior to be used in importance sampling. Multiple choices are allowed.
return_all_coverages	return raw results i.e. coverages for each simulations. When FALSE (default), summary statistics are returned.
...	additional arguments to arima_pi.

Value

a list containing the coverage probabilities

See Also

arima_pi.

Examples

## Not run: 
set.seed(123)
# takes a while, notice se, increase nsim2 to get more accurate results
avg_coverage_arima(phi = 0.9, n = 50, n_ahead = 10, nsim2 = 100)

avg_coverage_arima(phi = 0.9, theta = -0.6, n = 50, n_ahead = 10, nsim2 = 100)

## End(Not run)

helske/tsPI documentation built on Sept. 9, 2023, 8:15 a.m.