A B C D E F G H I L M N P Q R S T U V W misc
| AIC.fitsimts | Akaike's Information Criterion | 
| AR | Create an Autoregressive P [AR(P)] Process | 
| AR1 | Definition of an Autoregressive Process of Order 1 | 
| ar1_to_wv | AR(1) process to WV | 
| ARIMA | Create an Autoregressive Integrated Moving Average (ARIMA) Process | 
| ARMA | Create an Autoregressive Moving Average (ARMA) Process | 
| ARMA11 | Definition of an ARMA(1,1) | 
| arma11_to_wv | ARMA(1,1) to WV | 
| arma_to_wv | ARMA process to WV | 
| australia | Quarterly Increase in Stocks Non-Farm Total, Australia | 
| auto_corr | Empirical ACF and PACF | 
| best_model | Select the Best Model | 
| check | Diagnostics on Fitted Time Series Model | 
| compare_acf | Comparison of Classical and Robust Correlation Analysis Functions | 
| corr_analysis | Correlation Analysis Functions | 
| derivative_first_matrix | Analytic D matrix of Processes | 
| deriv_2nd_ar1 | Analytic second derivative matrix for AR(1) process | 
| deriv_2nd_arma11 | Analytic D matrix for ARMA(1,1) process | 
| deriv_2nd_dr | Analytic second derivative matrix for drift process | 
| deriv_2nd_ma1 | Analytic second derivative for MA(1) process | 
| deriv_ar1 | Analytic D matrix for AR(1) process | 
| deriv_arma11 | Analytic D matrix for ARMA(1,1) process | 
| deriv_dr | Analytic D matrix for Drift (DR) Process | 
| deriv_ma1 | Analytic D matrix for MA(1) process | 
| deriv_qn | Analytic D matrix for Quantization Noise (QN) Process | 
| deriv_rw | Analytic D matrix Random Walk (RW) Process | 
| deriv_wn | Analytic D Matrix for a Gaussian White Noise (WN) Process | 
| diag_boxpierce | Box-Pierce | 
| diag_ljungbox | Ljung-Box | 
| diag_plot | Diagnostic Plot of Residuals | 
| diag_portmanteau_ | Portmanteau Tests | 
| DR | Create an Drift (DR) Process | 
| dr_to_wv | Drift to WV | 
| estimate | Fit a Time Series Model to Data | 
| evaluate | Evalute a time series or a list of time series models | 
| FGN | Definition of a Fractional Gaussian Noise (FGN) Process | 
| gen_ar1blocks | Generate AR(1) Block Process | 
| gen_bi | Generate Bias-Instability Process | 
| gen_gts | Simulate a simts TS object using a theoretical model | 
| gen_lts | Generate a Latent Time Series Object Based on a Model | 
| gen_nswn | Generate Non-Stationary White Noise Process | 
| GM | Create a Gauss-Markov (GM) Process | 
| gmwm | Generalized Method of Wavelet Moments (GMWM) | 
| gmwm_imu | GMWM for (Robust) Inertial Measurement Units (IMUs) | 
| gts | Create a simts TS object using time series data | 
| hydro | Mean Monthly Precipitation, from 1907 to 1972 | 
| imu | Create an IMU Object | 
| imu_time | Pulls the IMU time from the IMU object | 
| is.gts | Is simts Object | 
| is.imu | Is simts Object | 
| is.lts | Is simts Object | 
| is.ts.model | Is simts Object | 
| lts | Generate a Latent Time Series Object from Data | 
| M | Definition of a Mean deterministic vector returned by the matrix by vector product of matrix X and vector beta | 
| MA | Create an Moving Average Q [MA(Q)] Process | 
| MA1 | Definition of an Moving Average Process of Order 1 | 
| ma1_to_wv | Moving Average Order 1 (MA(1)) to WV | 
| make_frame | Default utility function for various plots titles | 
| MAPE | Median Absolute Prediction Error | 
| MAT | Definition of a Matérn Process | 
| np_boot_sd_med | Bootstrap standard error for the median | 
| plot.gmwm | Plot the GMWM with the Wavelet Variance | 
| plot.PACF | Plot Partial Auto-Covariance and Correlation Functions | 
| plot.simtsACF | Plot Auto-Covariance and Correlation Functions | 
| plot_pred | Plot Time Series Forecast Function | 
| PLP | Definition of a Power Law Process | 
| predict.fitsimts | Time Series Prediction | 
| predict.gmwm | Predict future points in the time series using the solution of the Generalized Method of Wavelet Moments | 
| QN | Create an Quantisation Noise (QN) Process | 
| qn_to_wv | Quantisation Noise (QN) to WV | 
| read.imu | Read an IMU Binary File into R | 
| resid_plot | Plot the Distribution of (Standardized) Residuals | 
| rgmwm | GMWM for Robust/Classical Comparison | 
| rtruncated_normal | Truncated Normal Distribution Sampling Algorithm | 
| RW | Create an Random Walk (RW) Process | 
| RW2dimension | Function to Compute Direction Random Walk Moves | 
| rw_to_wv | Random Walk to WV | 
| SARIMA | Create a Seasonal Autoregressive Integrated Moving Average (SARIMA) Process | 
| SARMA | Create a Seasonal Autoregressive Moving Average (SARMA) Process | 
| savingrt | Personal Saving Rate | 
| select | Time Series Model Selection | 
| select_ar | Run Model Selection Criteria on ARIMA Models | 
| select_arima | Run Model Selection Criteria on ARIMA Models | 
| select_arma | Run Model Selection Criteria on ARIMA Models | 
| select_ma | Run Model Selection Criteria on ARIMA Models | 
| simple_diag_plot | Basic Diagnostic Plot of Residuals | 
| simplified_print_SARIMA | Simplify and print SARIMA model | 
| SIN | Definition of a Sinusoidal (SIN) Process | 
| summary.fitsimts | Summary of fitsimts object | 
| summary.gmwm | Summary of GMWM object | 
| theo_acf | Theoretical Autocorrelation (ACF) of an ARMA process | 
| theo_pacf | Theoretical Partial Autocorrelation (PACF) of an ARMA process | 
| update.gmwm | Update (Robust) GMWM object for IMU or SSM | 
| update.gts | Update Object Attribute | 
| update.imu | Update Object Attribute | 
| update.lts | Update Object Attribute | 
| value | Obtain the value of an object's properties | 
| value.imu | Obtain the value of an object's properties | 
| WN | Create an White Noise (WN) Process | 
| wn_to_wv | Gaussian White Noise to WV | 
| [.imu | Subset an IMU Object |