A B C D F G I K L M N O P R S T U V Z
| tsDyn-package | Getting started with the tsDyn package | 
| AAR | Additive nonlinear autoregressive model | 
| aar | Additive nonlinear autoregressive model | 
| accuracy_stat | Forecasting accuracy measures. | 
| accuracy_stat.default | Forecasting accuracy measures. | 
| accuracy_stat.pred_roll | Forecasting accuracy measures. | 
| addRegime | addRegime test | 
| AIC.nlar | NLAR methods | 
| ar_mean | Long-term mean of an AR(p) process | 
| ar_mean.linear | Long-term mean of an AR(p) process | 
| ar_mean.lstar | Long-term mean of an AR(p) process | 
| ar_mean.setar | Long-term mean of an AR(p) process | 
| as.data.frame.llar | Locally linear model | 
| as.data.frame.rank.select | Selection of the cointegrating rank with Information criterion. | 
| autopairs | Bivariate time series plots | 
| autotriples | Trivariate time series plots | 
| autotriples.rgl | Interactive trivariate time series plots | 
| availableModels | Available models | 
| barry | Time series of PPI used as example in Bierens and Martins (2010) | 
| BBCTest | Test of unit root against SETAR alternative | 
| BIC.nlar | NLAR methods | 
| charac_root | Characteristic roots of the AR coefficients | 
| charac_root.nlar | Characteristic roots of the AR coefficients | 
| coef.nlar | NLAR methods | 
| coefA | Extract cointegration parameters A, B and PI | 
| coefA.ca.jo | Extract cointegration parameters A, B and PI | 
| coefA.VECM | Extract cointegration parameters A, B and PI | 
| coefB | Extract cointegration parameters A, B and PI | 
| coefB.ca.jo | Extract cointegration parameters A, B and PI | 
| coefB.VECM | Extract cointegration parameters A, B and PI | 
| coefPI | Extract cointegration parameters A, B and PI | 
| d2sigmoid | sigmoid functions | 
| delta | delta test of conditional independence | 
| delta.lin | delta test of linearity | 
| delta.lin.test | delta test of linearity | 
| delta.test | delta test of conditional independence | 
| deviance.nlar | NLAR methods | 
| dsigmoid | sigmoid functions | 
| fevd.nlVar | Forecast Error Variance Decomposition | 
| fitted | fitted method for objects of class nlVar, i.e. VAR and VECM models. | 
| fitted.nlar | NLAR methods | 
| fitted.nlVar | fitted method for objects of class nlVar, i.e. VAR and VECM models. | 
| getTh | Extract threshold(s) coefficient | 
| getTh.default | Extract threshold(s) coefficient | 
| GIRF | Generalized Impulse response Function (GIRF) | 
| GIRF.linear | Generalized Impulse response Function (GIRF) | 
| GIRF.nlVar | Generalized Impulse response Function (GIRF) | 
| GIRF.setar | Generalized Impulse response Function (GIRF) | 
| IIPUs | US monthly industrial production from Hansen (1999) | 
| irf.ar | Impulse response function | 
| irf.linear | Impulse response function | 
| irf.nlVar | Impulse response function | 
| irf.setar | Impulse response function | 
| irf.TVAR | Impulse response function | 
| irf.TVECM | Impulse response function | 
| irf.VAR | Impulse response function | 
| irf.VECM | Impulse response function | 
| isLinear | isLinear | 
| KapShinTest | Test of unit root against SETAR alternative with | 
| lags.select | Selection of the lag with Information criterion. | 
| LINEAR | Linear AutoRegressive models | 
| linear | Linear AutoRegressive models | 
| linear.boot | Simulation and bootstrap of Threshold Autoregressive model (SETAR) | 
| linear.sim | Simulation and bootstrap of Threshold Autoregressive model (SETAR) | 
| lineVar | Multivariate linear models: VAR and VECM | 
| llar | Locally linear model | 
| llar.fitted | Locally linear model | 
| llar.predict | Locally linear model | 
| logLik.nlVar | Extract Log-Likelihood | 
| logLik.VAR | Extract Log-Likelihood | 
| logLik.VECM | Extract Log-Likelihood | 
| LSTAR | Logistic Smooth Transition AutoRegressive model | 
| lstar | Logistic Smooth Transition AutoRegressive model | 
| m.unrate | Monthly US unemployment | 
| MakeThSpec | Specification of the threshold search | 
| makeThSpec | Specification of the threshold search | 
| MAPE | Mean Absolute Percent Error | 
| MAPE.default | Mean Absolute Percent Error | 
| MAPE.nlar | NLAR methods | 
| mse | Mean Square Error | 
| mse.default | Mean Square Error | 
| mse.nlar | NLAR methods | 
| nlar-methods | NLAR methods | 
| NNET | Neural Network nonlinear autoregressive model | 
| nnetTs | Neural Network nonlinear autoregressive model | 
| OlsTVAR | Multivariate Threshold Vector Autoregressive model | 
| plot-methods | Plotting methods for SETAR and LSTAR subclasses | 
| plot.aar | Additive nonlinear autoregressive model | 
| plot.GIRF_df | Generalized Impulse response Function (GIRF) | 
| plot.llar | Locally linear model | 
| plot.lstar | Plotting methods for SETAR and LSTAR subclasses | 
| plot.nlar | NLAR methods | 
| plot.setar | Plotting methods for SETAR and LSTAR subclasses | 
| plot_ECT | Plot the Error Correct Term (ECT) response | 
| predict | Predict method for objects of class "nlar". | 
| predict.nlar | Predict method for objects of class "nlar". | 
| predict.TVAR | Predict method for objects of class "VAR", "VECM" or "TVAR" | 
| predict.VAR | Predict method for objects of class "VAR", "VECM" or "TVAR" | 
| predict.VECM | Predict method for objects of class "VAR", "VECM" or "TVAR" | 
| predict_rolling | Rolling forecasts | 
| predict_rolling.nlVar | Rolling forecasts | 
| print.aar | Additive nonlinear autoregressive model | 
| print.linear | Linear AutoRegressive models | 
| print.llar | Locally linear model | 
| print.rank.select | Selection of the cointegrating rank with Information criterion. | 
| print.rank.test | Test of the cointegrating rank | 
| print.summary.linear | Linear AutoRegressive models | 
| rank.select | Selection of the cointegrating rank with Information criterion. | 
| rank.test | Test of the cointegrating rank | 
| regime | Extract a variable showing the regime | 
| regime.default | Extract a variable showing the regime | 
| regime.lstar | Extract a variable showing the regime | 
| resample_vec | Resampling schemes | 
| residuals.nlar | NLAR methods | 
| resVar | Residual variance | 
| selectLSTAR | Automatic selection of model hyper-parameters | 
| selectNNET | Automatic selection of model hyper-parameters | 
| selectSETAR | Automatic selection of SETAR hyper-parameters | 
| selectSetar | Automatic selection of SETAR hyper-parameters | 
| selectsetar | Automatic selection of SETAR hyper-parameters | 
| SETAR | Self Threshold Autoregressive model | 
| setar | Self Threshold Autoregressive model | 
| setar.boot | Simulation and bootstrap of Threshold Autoregressive model (SETAR) | 
| setar.sim | Simulation and bootstrap of Threshold Autoregressive model (SETAR) | 
| setarTest | Test of linearity against threshold (SETAR) | 
| setartest | Test of linearity against threshold (SETAR) | 
| setarTest_IIPUs_results | Results from the setarTest, applied on Hansen (1999) data | 
| sigmoid | sigmoid functions | 
| STAR | STAR model | 
| star | STAR model | 
| summary.aar | Additive nonlinear autoregressive model | 
| summary.linear | Linear AutoRegressive models | 
| summary.nlar | NLAR methods | 
| summary.rank.select | Selection of the cointegrating rank with Information criterion. | 
| summary.rank.test | Test of the cointegrating rank | 
| summary.setar | Self Threshold Autoregressive model | 
| toLatex.nlar | NLAR methods | 
| toLatex.setar | Latex representation of fitted setar models | 
| tsDyn | Getting started with the tsDyn package | 
| TVAR | Multivariate Threshold Vector Autoregressive model | 
| TVAR.boot | Simulation of a multivariate Threshold Autoregressive model (TVAR) | 
| TVAR.LRtest | Test of linearity | 
| TVAR.sim | Simulation of a multivariate Threshold Autoregressive model (TVAR) | 
| TVECM | Threshold Vector Error Correction model (VECM) | 
| TVECM.boot | Simulation and bootstrap a VECM or bivariate TVECM | 
| TVECM.HStest | Test of linear cointegration vs threshold cointegration | 
| TVECM.SeoTest | No cointegration vs threshold cointegration test | 
| TVECM.sim | Simulation and bootstrap a VECM or bivariate TVECM | 
| UsUnemp | US unemployment series used in Caner and Hansen (2001) | 
| VAR.boot | Simulate or bootstrap a VAR model | 
| VAR.sim | Simulate or bootstrap a VAR model | 
| VARrep | VAR representation | 
| VARrep.VAR | VAR representation | 
| VARrep.VECM | VAR representation | 
| VECM | Estimation of Vector error correction model (VECM) | 
| VECM.boot | Simulation and bootstrap a VECM or bivariate TVECM | 
| VECM.sim | Simulation and bootstrap a VECM or bivariate TVECM | 
| VECM_symbolic | Virtual VECM model | 
| zeroyld | zeroyld time series | 
| zeroyldMeta | zeroyld time series |