Rao_test: Perform Rao's score test for a GSMVAR model

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

Perform Rao's score test for a GSMVAR model

Description

Rao_test performs Rao's score test for a GSMVAR model

Usage

Rao_test(gsmvar)

Arguments

gsmvar

an object of class 'gsmvar' generated by fitGSMVAR or GSMVAR, containing the model specified by the null hypothesis (i.e., the constrained model).

Details

Tests the constraints imposed in the model given in the argument GSMVAR. This implementation uses the outer product of gradients approximation in the test statistic.

Value

A list with class "hypotest" containing the test results and arguments used to calculate the test.

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 Unpublished working paper, available as arXiv:2007.04713.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 Unpublished working paper, available as arXiv:2109.13648.

@keywords internal

See Also

LR_test, Wald_test, fitGSMVAR, GSMVAR, diagnostic_plot, profile_logliks

Examples

## These are long running examples that use parallel computing!
## The below examples take around 30 seconds to run.

# Structural GMVAR(2, 2), d=2 model with recursive identification
# with the AR matrices  restricted to be the identical across the regimes:
W22 <- matrix(c(1, NA, 0, 1), nrow=2, byrow=FALSE)
C_mat <- rbind(diag(2*2^2), diag(2*2^2))
fit22sc <- fitGSMVAR(gdpdef, p=2, M=2, constraints=C_mat,
                     structural_pars=list(W=W22), ncalls=1, seeds=1)

# Test the null:
Rao_test(fit22sc)

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