R: Improved Prediction Intervals for ARIMA Processes and Structural Time Series

# Improved Prediction Intervals for ARIMA Processes and Structural Time Series

## Documentation for package ‘tsPI’ version 1.0.4

- DESCRIPTION file

## Help Pages

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