regime_distance: Calculate "distance" between two (scaled) regimes...

In gmvarkit: Estimate Gaussian and Student's t Mixture Vector Autoregressive Models

Calculate "distance" between two (scaled) regimes \upsilon_{m} = (\phi_{m,0},\phi_{m},\sigma_{m})

Description

regime_distance calculates "distance" between two scaled regimes. This is used in the genetic algorithm.

Usage

regime_distance(regime_pars1, regime_pars2)

Arguments

regime_pars1	a length pd^2+d+d(d+1)/2 vector \upsilon_{m} = (\phi_{m,0},\phi_{m},\sigma_{m}).
regime_pars2	a length pd^2+d+d(d+1)/2 vector \upsilon_{m} = (\phi_{m,0},\phi_{m},\sigma_{m}).

Value

Returns "distance" between regime_pars1 and regime_pars2. Values are scaled before calculating the "distance". Read the source code for more details.

Warning

No argument checks!

References

• Kalliovirta L., Meitz M. and Saikkonen P. 2016. Gaussian mixture vector autoregression. Journal of Econometrics, 192, 485-498.

• Virolainen S. 2022. Structural Gaussian mixture vector autoregressive model with application to the asymmetric effects of monetary policy shocks. Unpublished working paper, available as arXiv:2007.04713.

• Virolainen S. 2022. Gaussian and Student's t mixture vector autoregressive model with application to the asymmetric effects of monetary policy shocks in the Euro area. Unpublished working paper, available as arXiv:2109.13648.

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gmvarkit documentation built on Nov. 15, 2023, 1:07 a.m.