GIRF_Proba_CI {EWS} | R Documentation |
From the results of the Simulation_GIRF function, this function calculates the values of the upper and lower bounds of the confidence intervals, as well as the average of the different response functions for the probability.
GIRF_Proba_CI(results_simul_GIRF, CI_bounds, n_simul, horizon_forecast)
results_simul_GIRF |
Matrix containing results of the Simulation_GIRF function. |
CI_bounds |
Numeric variable between 0 and 1 for the size of the confidence intervals. |
n_simul |
Numeric variable equal to the total number of replications. |
horizon_forecast |
Numeric variable corresponding to the horizon target for the GIRF analysis. |
A list with:
horizon |
Numeric vector containing the horizon targer. |
Simulation_CI_proba_shock |
a matrix containing the set of simulations of probabilities with shock belonging to the confidence interval. |
Simulation_CI_proba |
a matrix containing the set of simulations of probabilities belonging to the confidence interval. |
CI_proba_shock |
a matrix containing three columns: the lower bound of the CI, the average of the IRFs, and the upper bound of the CI for the probabilities with shock. |
CI_proba |
a matrix containing three columns: the lower bound of the CI, the average of the IRFs, and the upper bound of the CI for the probabilities. |
Jean-Baptiste Hasse and Quentin Lajaunie
Lajaunie, Quentin. Generalized Impulse Response Function for Dichotomous Models. No. 2852. Orleans Economics Laboratory/Laboratoire d'Economie d'Orleans (LEO), University of Orleans, 2021.
# NOT RUN {
# Import data
data("data_USA")
# Data process
Var_Y <- as.vector(data_USA$NBER)
Var_X <- as.vector(data_USA$Spread)
# Simulation for the GIRF analysis
results_simulation <- Simul_GIRF(Var_Y, Var_X, TRUE, 1, 1, 2, 0.95, 3, "AM")
# Confidence intervals for the index
results <- GIRF_Proba_CI(results_simulation, 0.95, 2, 3)
# print results
results
#}