ModalForecast: Parametric Modal ARIMA Models using the SKD Family
Implements parametric modal Autoregressive Integrated Moving Average (ARIMA) models utilizing the Skewed Distribution (SKD) family. Current distributions supported are the Skew-Normal, Skewed Student-t, and Skewed Laplace. The conditional mode is parameterized and optimized via maximum likelihood using analytical gradients. Includes comprehensive residual diagnostics, robustness options (heavy tails, asymmetry), robust parametric bootstrap prediction intervals, and classical asymptotic inference via the Fisher Information matrix. Methods are described in Galarza, C.E., Lachos, V.H., Cabral, C.R.B., & Castro, L.M. (2017) <doi:10.1002/sta4.140>.
| Version: |
0.1.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
stats, graphics, forecast, ggplot2, gridExtra, scales, grid |
| Suggests: |
rmarkdown, testthat (≥ 3.0.0), knitr |
| Published: |
2026-05-12 |
| DOI: |
10.32614/CRAN.package.ModalForecast (may not be active yet) |
| Author: |
Christian Galarza [aut, cre] |
| Maintainer: |
Christian Galarza <chedgala at espol.edu.ec> |
| BugReports: |
https://github.com/chedgala/ModalForecast/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/chedgala/ModalForecast |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| In views: |
TimeSeries |
| CRAN checks: |
ModalForecast results |
Documentation:
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