R: Time Series Analysis Tools

# Time Series Analysis Tools

## Documentation for package ‘simts’ version 0.2.4

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

A B C D E F G H I L M N P Q R S T U V W misc

## -- A --

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

## -- B --

best_model | Select the Best Model

## -- C --

check | Diagnostics on Fitted Time Series Model
compare_acf | Comparison of Classical and Robust Correlation Analysis Functions
corr_analysis | Correlation Analysis Functions

## -- D --

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

## -- E --

estimate | Fit a Time Series Model to Data
evaluate | Evalute a time series or a list of time series models

## -- F --

FGN | Definition of a Fractional Gaussian Noise (FGN) Process

## -- G --

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

## -- H --

hydro | Mean Monthly Precipitation, from 1907 to 1972

## -- I --

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

## -- L --

lts | Generate a Latent Time Series Object from Data

## -- M --

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

## -- N --

np_boot_sd_med | Bootstrap standard error for the median

## -- P --

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

## -- Q --

QN | Create an Quantisation Noise (QN) Process
qn_to_wv | Quantisation Noise (QN) to WV

## -- R --

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

## -- S --

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

## -- T --

theo_acf | Theoretical Autocorrelation (ACF) of an ARMA process
theo_pacf | Theoretical Partial Autocorrelation (PACF) of an ARMA process

## -- U --

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

## -- V --

value | Obtain the value of an object's properties
value.imu | Obtain the value of an object's properties

## -- W --

WN | Create an White Noise (WN) Process
wn_to_wv | Gaussian White Noise to WV

## -- misc --

[.imu | Subset an IMU Object