Package: forecastSNSTS 1.2-0.9000
Tobias Kley
forecastSNSTS: Forecasting for Stationary and Non-Stationary Time Series
Methods to compute linear h-step ahead prediction coefficients based on localised and iterated Yule-Walker estimates and empirical mean squared and absolute prediction errors for the resulting predictors. Also, functions to compute autocovariances for AR(p) processes, to simulate tvARMA(p,q) time series, and to verify an assumption from Kley et al. (2017), Preprint <http://personal.lse.ac.uk/kley/forecastSNSTS.pdf>.
Authors:
forecastSNSTS_1.2-0.9000.tar.gz
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forecastSNSTS.pdf |forecastSNSTS.html✨
forecastSNSTS/json (API)
NEWS
| # Install 'forecastSNSTS' in R: |
| install.packages('forecastSNSTS', repos = c('https://tobiaskley.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tobiaskley/forecastsnsts/issues
Last updated 7 years agofrom:484fed0c1f. Checks:OK: 1 NOTE: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 04 2024 |
| R-4.5-win-x86_64 | NOTE | Nov 04 2024 |
| R-4.5-linux-x86_64 | NOTE | Nov 04 2024 |
| R-4.4-win-x86_64 | NOTE | Nov 04 2024 |
| R-4.4-mac-x86_64 | NOTE | Nov 04 2024 |
| R-4.4-mac-aarch64 | NOTE | Nov 04 2024 |
| R-4.3-win-x86_64 | NOTE | Nov 04 2024 |
| R-4.3-mac-x86_64 | NOTE | Nov 04 2024 |
| R-4.3-mac-aarch64 | NOTE | Nov 04 2024 |
Exports:acfARpfMSPEpredCoeftvARMA
Dependencies:Rcpp
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Forecasting of Stationary and Non-Stationary Time Series | forecastSNSTS-package forecastSNSTS |
| Compute autocovariances of an AR(p) process | acfARp |
| Mean Squared Prediction Errors, for a single h | computeMSPEcpp |
| Compute f(delta) for a tvAR(p) process | f |
| Mean squared or absolute h-step ahead prediction errors | MAPE measure-of-accuracy MSPE |
| Plot a 'MSPE' or 'MAPE' object | plot.MAPE plot.measure-of-accuracy plot.MSPE |
| h-step Prediction coefficients | predCoef |
| Simulation of an tvARMA(p) time series. | ts-models-tvARMA tvARMA |
| Workhorse function for tvARMA time series generation | tvARMAcpp |