| ACMx | Estimation of Autoregressive Condtional Mean Models |
| backTAR | Backtest for Univariate TAR Models |
| backtest | Backtest |
| clutterKF | Kalman Filter for Tracking in Clutter |
| cvlm | Check linear models with cross validation |
| est_cfar | Estimation of a CFAR Process |
| est_cfarh | Estimation of a CFAR Process with Heteroscedasticity and... |
| F.test | F Test for Nonlinearity |
| F_test_cfar | F Test for a CFAR Process |
| F_test_cfarh | F Test for a CFAR Process with Heteroscedasticity and... |
| g_cfar | Generate a CFAR Process |
| g_cfar1 | Generate a CFAR(1) Process |
| g_cfar2 | Generate a CFAR(2) Process |
| g_cfar2h | Generate a CFAR(2) Process with Heteroscedasticity and... |
| hfDummy | Create Dummy Variables for High-Frequency Intraday... |
| MKF.Full.RB | Full Information Propagation Step under Mixture Kalman Filter |
| MKFstep.fading | One Propagation Step under Mixture Kalman Filter for Fading... |
| MSM.fit | Fitting Univariate Autoregressive Markov Switching Models |
| MSM.sim | Generate Univeraite 2-regime Markov Switching Models |
| mTAR | Estimation of a Multivariate Two-Regime SETAR Model |
| mTAR.est | Estimation of Multivariate TAR Models |
| mTAR.pred | Prediction of A Fitted Multivariate TAR Model |
| mTAR.sim | Generate Two-Regime (VAR) Models |
| NNsetting | Setting Up The Predictor Matrix in A Neural Network for Time... |
| p_cfar | Prediction of CFAR Processes |
| p_cfar_part | Partial Curve Prediction of CFAR Processes |
| PRnd | ND Test |
| rankQ | Rank-Based Portmanteau Tests |
| rcAR | Estimating of Random-Coefficient AR Models |
| ref.mTAR | Refine A Fitted 2-Regime Multivariate TAR Model |
| simPassiveSonar | Simulate A Sample Trajectory |
| simu_fading | Simulate Signals from A System with Rayleigh Flat-Fading... |
| simuTargetClutter | Simulate A Moving Target in Clutter |
| SISstep.fading | Sequential Importance Sampling Step for Fading Channels |
| SMC | Generic Sequential Monte Carlo Method |
| SMC.Full | Generic Sequential Monte Carlo Using Full Information... |
| SMC.Full.RB | Generic Sequential Monte Carlo Using Full Information... |
| SMC.Smooth | Generic Sequential Monte Carlo Smoothing with Marginal... |
| Sstep.Clutter | Sequential Monte Carlo for A Moving Target under Clutter... |
| Sstep.Clutter.Full | Sequential Importance Sampling under Clutter Environment |
| Sstep.Clutter.Full.RB | Sequential Importance Sampling under Clutter Environment |
| Sstep.Smooth.Sonar | Sequential Importance Sampling for A Target with Passive... |
| Sstep.Sonar | Sequential Importance Sampling Step for A Target with Passive... |
| thr.test | Threshold Nonlinearity Test |
| Tsay | Tsay Test for Nonlinearity |
| tvAR | Estimate Time-Varying Coefficient AR Models |
| tvARFiSm | Filtering and Smoothing for Time-Varying AR Models |
| uTAR | Estimation of a Univariate Two-Regime SETAR Model |
| uTAR.est | General Estimation of TAR Models |
| uTAR.grid | Search for Threshold Value of A Two-Regime SETAR Model |
| uTAR.pred | Prediction of A Fitted Univariate TAR Model |
| uTAR.sim | Generate Univariate SETAR Models |
| wrap.SMC | Sequential Monte Carlo Using Sequential Importance Sampling... |
