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GAS (version 0.1.1)

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), ...)

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.

Value

array of dimension iT+1 x B x K, where iT 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. Also the one step ahead prediction is reported, this why iT + 1.

Details

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

References

Blasques, F., Koopman, S. J., Lasak, K., & 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.

Examples

Run this code
## Not run: 
# # 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)
# 
# ## End(Not run)

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