Improved Prediction Intervals for ARIMA Processes and Structural Time Series

Documentation for package ‘tsPI’ version 1.0.4

acv_arma	Compute a theoretical autocovariance function of ARMA process
approx_joint_jeffreys	Compute different types of importance weights based on Jeffreys's prior
approx_marginal_jeffreys	Compute different types of importance weights based on Jeffreys's prior
arima_pi	Prediction Intervals for ARIMA Processes with Exogenous Variables Using Importance Sampling
avg_coverage_arima	Compute the average coverage of the prediction intervals computed by naive plug-in method and 'arima_pi'
avg_coverage_struct	Compute the average coverage of the prediction intervals computed by 'struct_pi' and plug-in method
dacv_arma	Compute the partial derivatives of theoretical autocovariance function of ARMA process
exact_joint_jeffreys	Compute different types of importance weights based on Jeffreys's prior
exact_marginal_jeffreys	Compute different types of importance weights based on Jeffreys's prior
information_arma	Large Sample Approximation of Information Matrix for ARMA process
jeffreys	Compute different types of importance weights based on Jeffreys's prior
struct_pi	Prediction Intervals for Structural Time Series with Exogenous Variables Using Importance Sampling
tsPI	Improved Prediction Intervals for ARIMA Processes and Structural Time Series