GAS (version 0.3.4.1)

ConfidenceBands: Build confidence bands for the filtered parameters

Description

Build confidence bands for the filtered parameters sampling the coefficients from the asymptotic distribution as in Blasques et al. (2016).

Usage

ConfidenceBands(object, B = 10000, probs = c(0.01,0.1,0.9,0.99), ...)

Value

An object of the class array of dimension (T+1) x B x K, where T is the length of the time series, K is the number of parameters and B the number of draws. The first slice reports the estimated filtered parameters. The one step ahead prediction is also reported, this why T+1.

Arguments

object

An object of the class uGASFit or mGASFit

B

numeric Number of draws from the asymptotic distributions.

probs

numeric Quantiles to returns.

...

Additional arguments.

Author

Leopoldo Catania

Details

This function implements the "In-Sample Simulation-Based Bands" Section 3.3 of Blasques et al. (2016).

References

Blasques F, Koopman SJ, Lasak K, and Lucas, A (2016). "In-sample Confidence Bands and Out-of-Sample Forecast Bands for Time-Varying Parameters in Observation-Driven Models." International Journal of Forecasting, 32(3), 875-887. tools:::Rd_expr_doi("10.1016/j.ijforecast.2016.04.002").

Examples

if (FALSE) {

# show the information of all the supported distributions
library("GAS")

data("cpichg")

GASSpec = UniGASSpec(Dist = "std", ScalingType = "Identity",
                     GASPar = list(location = TRUE, scale = TRUE,
                                   shape = FALSE))

Fit = UniGASFit(GASSpec, cpichg)

Bands = ConfidenceBands(Fit)
}