GAfit |
Genetic algorithm for preliminary estimation of a GMVAR model |
get_alpha_mt |
Get mixing weights alpha_mt (this function is for internal use) |
get_boldA_eigens |
Calculate absolute values of the eigenvalues of the "bold A" matrices containing the AR coefficients |
get_foc |
Calculate gradient or Hessian matrix |
get_gradient |
Calculate gradient or Hessian matrix |
get_hessian |
Calculate gradient or Hessian matrix |
get_IC |
Calculate AIC, HQIC, and BIC |
get_minval |
Returns the default smallest allowed log-likelihood for given data. |
get_omega_eigens |
Calculate the eigenvalues of the "Omega" error term covariance matrices |
get_regime_autocovs |
Calculate regimewise autocovariance matrices |
get_regime_autocovs_int |
Calculate regimewise autocovariance matrices |
get_regime_means |
Calculate regime means mu_{m} |
get_regime_means_int |
Calculate regime means mu_{m} |
get_Sigmas |
Calculate the dp-dimensional covariance matrices Sigma_{m,p} in the mixing weights of the GMVAR model. |
get_soc |
Calculate gradient or Hessian matrix |
get_test_Omega |
Compute covariance matrix Omega used in quantile residual tests |
get_unconstrained_structural_pars |
Get structural parameters that indicate there are no constraints |
GIRF |
Estimate generalized impulse response function for a structural GMVAR model. |
GMVAR |
Create a class 'gmvar' object defining a reduced form or structural GMVAR model |
gmvarkit |
gmvarkit: Estimate Gaussian Mixture Vector Autoregressive (GMVAR) model |
gmvar_to_sgmvar |
Switch from two-regime reduced form GMVAR model to a structural GMVAR model. |
pick_allA |
Pick coefficient all matrices |
pick_all_phi0_A |
Pick all phi_{m,0} or mu_{m} and A_{m,1},...,A_{m,p} parameter values |
pick_alphas |
Pick mixing weight parameters alpha_{m}, m=1,...,M |
pick_Am |
Pick coefficient matrices |
pick_Ami |
Pick coefficient matrix |
pick_lambdas |
Pick the structural parameters eigenvalue 'lambdas' |
pick_Omegas |
Pick covariance matrices |
pick_phi0 |
Pick phi_{m,0} or mu_{m}, m=1,..,M vectors |
pick_regime |
Pick regime parameters *upsilon_{m}* = (phi_{m,0},*phi_{m}*,sigma_{m}) |
pick_W |
Pick the structural parameter matrix W |
plot.girf |
Estimate generalized impulse response function for a structural GMVAR model. |
plot.gmvar |
Create a class 'gmvar' object defining a reduced form or structural GMVAR model |
plot.gmvarpred |
plot method for class 'gmvarpred' objects |
plot.qrtest |
Quantile residual tests |
predict.gmvar |
Predict method for class 'gmvar' objects |
print.girf |
Estimate generalized impulse response function for a structural GMVAR model. |
print.gmvar |
Create a class 'gmvar' object defining a reduced form or structural GMVAR model |
print.gmvarpred |
Print method for class 'gmvarpred' objects |
print.gmvarsum |
Summary print method from objects of class 'gmvarsum' |
print.lr |
Perform likelihood ratio test for a GMVAR or SGMVAR model |
print.qrtest |
Quantile residual tests |
print.wald |
Perform Wald test for a GMVAR or SGMVAR model |
print_std_errors |
Print standard errors of GMVAR model in the same form as the model estimates are printed |
profile_logliks |
Plot profile log-likehoods around the estimates |
random_coefmats |
Create random VAR-model (dxd) coefficient matrices A. |
random_coefmats2 |
Create random stationary VAR model (dxd) coefficient matrices A. |
random_covmat |
Create random VAR model error term covariance matrix |
random_ind |
Create random mean-parametrized parameter vector of a GMVAR model that may not be stationary |
random_ind2 |
Create somewhat random parameter vector of a GMVAR model that is always stationary |
redecompose_Omegas |
In the decomposition of the covariance matrices (Muirhead, 1982, Theorem A9.9), change the order of the covariance matrices. |
reform_constrained_pars |
Reform constrained parameter vector into the "standard" form |
reform_data |
Reform data |
reform_structural_pars |
Reform structural parameter vector into the "standard" form |
regime_distance |
Calculate "distance" between two (scaled) regimes *upsilon_{m}* = (phi_{m,0},*phi_{m}*,sigma_{m}) |
reorder_W_columns |
Reorder columns of the W-matrix and lambda parameters of a structural GMVAR model. |
residuals.gmvar |
Create a class 'gmvar' object defining a reduced form or structural GMVAR model |
simulateGMVAR |
Simulate from GMVAR process |
smart_covmat |
Create random VAR-model (dxd) error term covariance matrix Omega fairly close to a given *positive definite* covariance matrix using (scaled) Wishart distribution |
smart_ind |
Create random parameter vector of a GMVAR model fairly close to a given parameter vector |
sort_and_standardize_alphas |
Sort mixing weight parameters in a decreasing order and standardize them to sum to one. |
sort_components |
Sort components in parameter vector according to mixing weights into a decreasing order |
sort_W_and_lambdas |
Sort the columns of W matrix by sorting the lambda parameters of the second regime to increasing order |
standard_errors |
Calculate standard errors for estimates of GMVAR model |
summary.gmvar |
Create a class 'gmvar' object defining a reduced form or structural GMVAR model |
swap_parametrization |
Swap the parametrization of a GMVAR model |
swap_W_signs |
Swap all signs in pointed columns a the W matrix of a structural GMVAR model. |
uncond_moments |
Calculate the unconditional mean, variance, the first p autocovariances, and the first p autocorrelations of a GMVAR process |
uncond_moments_int |
Calculate the unconditional mean, variance, the first p autocovariances, and the first p autocorrelations of a GMVAR process |
unvec |
Reverse vectorization operator |
unvech |
Reverse operator of the parsimonious vectorization operator 'vech' |
unWvec |
Reverse vectorization operator that restores zeros |
update_numtols |
Update the stationarity and positive definiteness numerical tolerances of an existing class 'gmvar' model. |