aa_gmvarkit-package |
gmvarkit: Estimate Gaussian Mixture Vector Autoregressive (GMVAR) model |
aa_gmvarkit |
gmvarkit: Estimate Gaussian Mixture Vector Autoregressive (GMVAR) model |
add_data |
Add data to object of class 'gmvar' defining a GMVAR model |
all_pos_ints |
Check whether all arguments are positive scalar whole numbers |
calc_gradient |
Calculate gradient or Hessian matrix |
calc_hessian |
Calculate gradient or Hessian matrix |
change_parametrization |
Change parametrization of the parameter vector |
change_regime |
Change regime parameters *upsilon_{m}* = (phi_{m,0},*phi_{m}*,sigma_{m}) of the given parameter vector. |
check_constraints |
Check the constraint matrix has the correct form |
check_data |
Check the data is in the correct form |
check_gmvar |
Checks whether the given object has class attribute "gmvar" |
check_null_data |
Checks whether the given object contains data or not |
check_parameters |
Check that the given parameter vector satisfies model assumptions |
check_pMd |
Check that p, M and d are correctly set |
diagnostic_plot |
Quantile residual diagnostic plot for GMVAR model |
dlogmultinorm |
Calculate logarithms of multiple multivariate normal densities with varying mean and constant covariance matrix |
eurusd |
Euro area and U.S. long-term government bond yields and Euro-U.S. dollar exchange rate. |
fitGMVAR |
Two-phase maximum likelihood estimation of GMVAR model |
format_valuef |
Function factory for value formatting |
form_boldA |
Form the ((dp)x(dp)) "bold A" matrices related to the VAR processes |
GAfit |
Genetic algorithm for preliminary estimation of GMVAR model |
get_boldA_eigens |
Calculate absolute values of the eigenvalues of the "bold A" matrices containing the AR coefficients |
get_gradient |
Calculate gradient or Hessian matrix |
get_hessian |
Calculate gradient or Hessian matrix |
get_IC |
Calculate AIC, HQIC and BIC |
get_regime_means |
Calculate and return regime means mu_{m} |
get_regime_means_int |
Calculate and return regime means mu_{m} |
get_test_Omega |
Compute covariance matrix Omega used in quantile residual tests |
GMVAR |
Create object of class 'gmvar' defining a GMVAR model |
in_paramspace |
Determine whether the parameter vector lies in the parameter space or not |
in_paramspace_int |
Determine whether the parameter vector lies in the parameter space or not |
is_stationary |
Check the stationary condition of given GMVAR model |
iterate_more |
Maximum likelihood estimation of GMVAR model with preliminary estimates |
logLik.gmvar |
Create object of class 'gmvar' defining a GMVAR model |
loglikelihood |
Compute log-likelihood of GMVAR model using parameter vector |
loglikelihood_int |
Compute the log-likelihood of Gaussian Mixture Vector Autoregressive model |
n_params |
Calculate the number of parameters in GMVAR model parameter vector |
pick_allA |
Pick coefficient all matrices |
pick_all_phi0_A |
Pick all phi_{m,0} or mu_{m} and A_{m} parameter values from the given parameter vector. |
pick_alphas |
Pick mixing weight parameters alpha_{m}, m=1,...,M from the given parameter vector. |
pick_Am |
Pick coefficient matrices |
pick_Ami |
Pick coefficient matrix |
pick_Omegas |
Pick covariance matrices |
pick_phi0 |
Pick phi_{m,0} or mu_{m}, m=1,..,M vectors from the given parameter vector |
pick_regime |
Pick regime parameters *upsilon_{m}* = (phi_{m,0},*phi_{m}*,sigma_{m}) from the given parameter vector. |
plot.gmvar |
Create object of class 'gmvar' defining a GMVAR model |
plot.gmvarpred |
plot method for class 'gmvarpred' objects |
plot.qrtest |
Quantile residual tests |
predict.gmvar |
Predict method for class 'gmvar' objects |
print.gmvar |
Create object of class 'gmvar' defining a GMVAR model |
print.gmvarpred |
print method for class 'gmvarpred' objects |
print.gmvarsum |
Summary print method from objects of class 'gmvarsum' |
print.qrtest |
Quantile residual tests |
print_std_errors |
Print standard errors of GMVAR model in the same form as the model estimates are printed |
quantile_residuals |
Calculate multivariate quantile residuals of GMVAR model |
quantile_residuals_int |
Calculate multivariate quantile residuals of GMVAR model |
quantile_residual_tests |
Quantile residual tests |
random_coefmats |
Create random VAR-model (dxd) coefficient matrices A. |
random_coefmats2 |
Create somewhat random stationary VAR model (dxd) coefficient matrices A. |
random_covmat |
Create somewhat random VAR model error term covariance matrix |
random_ind |
Create somewhat random mean-parametrized parameter vector of GMVAR model, that may not be stationary! |
random_ind2 |
Create somewhat random parameter vector of GMVAR model that is always stationary |
reform_constrained_pars |
Reform constrained parameter vector into the "standard" form |
reform_data |
Reform data |
regime_distance |
Calculate "distance" between two (scaled) regimes *upsilon_{m}* = (phi_{m,0},*phi_{m}*,sigma_{m}) |
residuals.gmvar |
Create object of class 'gmvar' defining a GMVAR model |
simulateGMVAR |
Simulate from GMVAR process |
smart_covmat |
Create somewhat 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 somewhat random parameter vector of GMVAR model fairly close to a given parameter vector |
sort_components |
Sort components in parameter vector by mixing weights into a decreasing order |
standard_errors |
Calculate standard errors for estimates of GMVAR model |
summary.gmvar |
Create object of class 'gmvar' defining a GMVAR model |
swap_parametrization |
Swap the parametrization of object of class 'gmvar' defining a GMVAR model |
unvec |
Reverse vectorization operator. |
unvech |
Reverse operator of the parsimonious vectorization operator 'vech()'. |
vec |
Vectorization operator. |
vech |
Parsimonious vectorization operator for symmetric matrices. |