| add_data | Add data to object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model |
| add_dfs | Add random dfs to a vector |
| all_pos_ints | Check whether all arguments are stricly positive natural numbers |
| alt_gsmar | Construct a GSMAR model based on results from an arbitrary estimation round of 'fitGSMAR' |
| calc_gradient | Calculate gradient or Hessian matrix |
| calc_hessian | Calculate gradient or Hessian matrix |
| changeRegime | Change the specified regime of parameter vector to the given regime-parameter vector |
| change_parametrization | Change parametrization of a parameter vector |
| checkAndCorrectData | Check that the data is set correctly and correct if not |
| checkConstraintMat | Check the constraint matrices |
| checkPM | Check that p and M are correctly set |
| check_data | Check that given object contains data |
| check_gsmar | Check that given object has class attribute 'gsmar' |
| check_model | Check that the argument 'model' is correctly specified. |
| check_params_length | Check that the parameter vector has the correct dimension |
| condmomentPlot | Condinional mean or variance plot for GMAR, StMAR, and G-StMAR models |
| condMoments | Calculate conditional moments of GMAR, StMAR, or G-StMAR model |
| diagnosticPlot | Quantile residual based diagnostic plots for GMAR, StMAR, and G-StMAR models |
| extractRegime | Extract regime from a parameter vector |
| fitGSMAR | Estimate Gaussian or Student's t Mixture Autoregressive model |
| format_valuef | Function factory for formatting values |
| GAfit | Genetic algorithm for preliminary estimation of GMAR, StMAR, or G-StMAR model |
| getOmega | Generate the covariance matrix Omega for quantile residual tests |
| get_ar_roots | Calculate absolute values of the roots of the AR characteristic polynomials |
| 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_regime_autocovs | Calculate regime specific autocovariances *gamma*_{m,p} |
| get_regime_means | Calculate regime specific means mu_{m} |
| get_regime_vars | Calculate regime specific variances gamma_{m,0} |
| get_soc | Calculate gradient or Hessian matrix |
| get_varying_h | Get differences 'h' which are adjusted for overly large degrees of freedom parameters |
| GSMAR | Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model |
| isIdentifiable | Check the stationarity and identification conditions of specified GMAR, StMAR, or G-StMAR model. |
| isStationary | Check the stationary condition of specified GMAR, StMAR, or G-StMAR model. |
| isStationary_int | Check the stationarity and identification conditions of specified GMAR, StMAR, or G-StMAR model. |
| iterate_more | Maximum likelihood estimation of GMAR, StMAR, or G-StMAR model with preliminary estimates |
| logLik.gsmar | Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model |
| loglikelihood | Compute the log-likelihood of GMAR, StMAR, or G-StMAR model |
| loglikelihood_int | Compute the log-likelihood of GMAR, StMAR, or G-StMAR model |
| mixingWeights | Calculate mixing weights of GMAR, StMAR or G-StMAR model |
| mixingWeights_int | Calculate mixing weights of a GMAR, StMAR, or G-StMAR model |
| nParams | Calculate the number of parameters |
| parameterChecks | Check the parameter vector is specified correctly |
| pick_alphas | Pick mixing weights parameters from parameter vector |
| pick_dfs | Pick degrees of freedom parameters from a parameter vector |
| pick_pars | Pick phi_0 (or mu), AR-coefficients, and variance parameters from a parameter vector |
| pick_phi0 | Pick phi0 or mean parameters from parameter vector |
| plot.gsmar | Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model |
| plot.gsmarpred | Plot method for class 'gsmarpred' objects |
| plot.qrtest | Quantile residual tests for GMAR, StMAR , and G-StMAR models |
| predict.gsmar | Forecast GMAR, StMAR, or G-StMAR process |
| print.gsmar | Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model |
| print.gsmarpred | Print method for class 'gsmarpred' objects |
| print.gsmarsum | Print method from objects of class 'gsmarsum' |
| print.qrtest | Quantile residual tests for GMAR, StMAR , and G-StMAR models |
| profile_logliks | Plot profile log-likehoods around the estimates |
| quantileResidualPlot | Plot quantile residual time series and histogram |
| quantileResiduals | Compute quantile residuals of GMAR, StMAR, or G-StMAR model |
| quantileResiduals_int | Compute quantile residuals of GMAR, StMAR, or G-StMAR model |
| quantileResidualTests | Quantile residual tests for GMAR, StMAR , and G-StMAR models |
| randomIndividual | Create random GMAR, StMAR, or G-StMAR model compatible parameter vector |
| randomIndividual_int | Create random GMAR, StMAR, or G-StMAR model compatible parameter vector |
| random_arcoefs | Create random AR coefficients |
| random_regime | Create random regime parameters |
| reformConstrainedPars | Reform parameter vector with linear constraints to correspond non-constrained parameter vector. |
| reformParameters | Reform any parameter vector into standard form. |
| reformRestrictedPars | Reform parameter vector with restricted autoregressive parameters to correspond non-restricted parameter vector. |
| regime_distance | Calculate "distance" between two regimes |
| removeAllConstraints | Transform constrained and restricted parameter vector into the regular form |
| residuals.gsmar | Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model |
| simudata | Simulated data |
| simulateGSMAR | Simulate values from GMAR, StMAR, and G-StMAR processes |
| smartIndividual | Create random GMAR, StMAR, or G-StMAR model compatible parameter vector |
| smartIndividual_int | Create random GMAR, StMAR, or G-StMAR model compatible parameter vector |
| sortComponents | Sort the mixture components of a GMAR, StMAR, or G-StMAR model |
| standardErrors | Calculate standard errors for estimates of a GMAR, StMAR, or GStMAR model |
| stmarpars_to_gstmar | Transform a StMAR model parameter vector to a corresponding G-StMAR model parameter vector with large dfs parameters reduced. |
| stmar_to_gstmar | Estimate a G-StMAR model based on a StMAR model with large degrees of freedom parameters |
| summary.gsmar | Create object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model |
| swap_parametrization | Swap the parametrization of object of class 'gsmar' defining a GMAR, StMAR, or G-StMAR model |
| T10Y1Y | Spread between 10-Year and 1-Year treasury rates: T10Y1Y |
| uGMAR | uGMAR: Estimate Univariate Gaussian and Student's t Mixture Autoregressive Models |
| uncondMoments | Calculate unconditional mean, variance, first p autocovariances and autocorrelations of the GSMAR process. |
| uncondMoments_int | Calculate unconditional mean, variance, and the first p autocovariances and autocorrelations of a GSMAR process. |
| warn_dfs | Warn about large degrees of freedom parameter values |