Time Series Analysis
Auto- and Cross- Covariance and -Correlation Function Estimation
Compute the Bootstrap Estimates of an ARIMA Model
Fitting an ARIMA model with Exogeneous Variables
Fitting an ARIMA model with Exogeneous Variables
Theoretical spectral density function of a stationary ARMA model
Selection of Subset ARMA Models
Determine the power transformation for serially correlated data
Additive Outlier Detection
Innovative Outlier Detection
Compute the sample extended acf (ESACF)
Fitted values of an arima model.
Simulate a GARCH process
Generalized Portmanteau Tests for GARCH Models
Construct harmonic functions for fitting harmonic trend model
Keenan's one-degree test for nonlinearity
Kurtosis
Lagged Regression Plot
Portmanteau Tests for Fitted ARIMA models
McLeod-Li test
Computing the periodogram
Compute and Plot the Forecasts Based on a Fitted Time Series Model
Plot the Best Subset ARMA models
Plot1
Prediction based on a fitted TAR model
Prewhiten a Bivariate Time Series, and Compute and Plot Their Sample C...
Simulate a first-order quadratic AR model
Compute the Standardized Residuals from a Fitted ARIMA Model
Runs test
Extract the season info from a time series
Skewness
Computing the spectrum
Summary of output from the armasubsets function
Estimation of a TAR model
Simulate a two-regime TAR model
Find the asympotitc behavior of the skeleton of a TAR model
Likelihood ratio test for threshold nonlinearity
Time Series Analysis
Tsay's Test for nonlinearity
Model Diagnostics for a Fitted ARIMAX Model
Model diagnostics for a fitted TAR model
Compute the lag of a vector.
Contains R functions and datasets detailed in the book "Time Series Analysis with Applications in R (second edition)" by Jonathan Cryer and Kung-Sik Chan.