Nonlinear Time Series Analysis
Estimation of Autoregressive Conditional Mean Models
Backtest for Univariate TAR Models
Backtest
Kalman Filter for Tracking in Clutter
Check linear models with cross validation
Estimation of a CFAR Process
Estimation of a CFAR Process with Heteroscedasticity and Irregualar Ob...
F Test for Nonlinearity
F Test for a CFAR Process
F Test for a CFAR Process with Heteroscedasticity and Irregular Observ...
Generate a CFAR Process
Generate a CFAR(1) Process
Generate a CFAR(2) Process
Generate a CFAR(2) Process with Heteroscedasticity and Irregular Obser...
Create Dummy Variables for High-Frequency Intraday Seasonality
Full Information Propagation Step under Mixture Kalman Filter
One Propagation Step under Mixture Kalman Filter for Fading Channels
Fitting Univariate Autoregressive Markov Switching Models
Generate Univariate 2-regime Markov Switching Models
Estimation of Multivariate TAR Models
Prediction of A Fitted Multivariate TAR Model
Estimation of a Multivariate Two-Regime SETAR Model
Generate Two-Regime (TAR) Models
Setting Up The Predictor Matrix in A Neural Network for Time Series Da...
Prediction of CFAR Processes
Partial Curve Prediction of CFAR Processes
ND Test
Rank-Based Portmanteau Tests
Estimating of Random-Coefficient AR Models
Refine A Fitted 2-Regime Multivariate TAR Model
Simulate A Sample Trajectory
Simulate Signals from A System with Rayleigh Flat-Fading Channels
Simulate A Moving Target in Clutter
Sequential Importance Sampling Step for Fading Channels
Generic Sequential Monte Carlo Using Full Information Proposal Distrib...
Generic Sequential Monte Carlo Using Full Information Proposal Distrib...
Generic Sequential Monte Carlo Method
Generic Sequential Monte Carlo Smoothing with Marginal Weights
Sequential Importance Sampling under Clutter Environment
Sequential Importance Sampling under Clutter Environment
Sequential Monte Carlo for A Moving Target under Clutter Environment
Sequential Importance Sampling for A Target with Passive Sonar
Sequential Importance Sampling Step for A Target with Passive Sonar
Threshold Nonlinearity Test
Tsay Test for Nonlinearity
Estimate Time-Varying Coefficient AR Models
Filtering and Smoothing for Time-Varying AR Models
General Estimation of TAR Models
Prediction of A Fitted Univariate TAR Model
Estimation of a Univariate Two-Regime SETAR Model
Generate Univariate SETAR Models
Sequential Monte Carlo Using Sequential Importance Sampling for Stocha...
Simulation, estimation, prediction procedure, and model identification methods for nonlinear time series analysis, including threshold autoregressive models, Markov-switching models, convolutional functional autoregressive models, nonlinearity tests, Kalman filters and various sequential Monte Carlo methods. More examples and details about this package can be found in the book "Nonlinear Time Series Analysis" by Ruey S. Tsay and Rong Chen, John Wiley & Sons, 2018 (ISBN: 978-1-119-26407-1).