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tsPI
View on CRAN: Click
here
Download and install tsPI package within the R console
Install from CRAN:
install.packages("tsPI")
Install from Github:
library("remotes")
install_github("cran/tsPI")
Install by package version:
library("remotes")
install_version("tsPI", "1.0.4")
Attach the package and use:
library("tsPI")
Maintained by
Jouni Helske
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-11-09
Latest Update: 2023-09-04
Description:
Prediction intervals for ARIMA and structural time series models using importance sampling approach with uninformative priors for model parameters, leading to more accurate coverage probabilities in frequentist sense. Instead of sampling the future observations and hidden states of the state space representation of the model, only model parameters are sampled, and the method is based solving the equations corresponding to the conditional coverage probability of the prediction intervals. This makes method relatively fast compared to for example MCMC methods, and standard errors of prediction limits can also be computed straightforwardly.
How to cite:
Jouni Helske (2015). tsPI: Improved Prediction Intervals for ARIMA Processes and Structural Time Series. R package version 1.0.4, https://cran.r-project.org/web/packages/tsPI
Previous versions and publish date:
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Other R packages that tsPI depends,
imports, suggests or enhances
Functions, R codes and Examples using
the tsPI R package
Some associated functions: acv_arma . arima_pi . avg_coverage_arima . avg_coverage_struct . dacv_arma . information_arma . priors . struct_pi . tsPI .
Some associated R codes: acv_arma.R . arima_pi.R . avg_coverage.R . avg_coverage_struct.R . information_arma.R . priors.R . struct_pi.R . tsPI-package.R . Full tsPI package functions and examples
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