wARMASVp: Winsorized ARMA Estimation for Higher-Order Stochastic
Volatility Models
Estimation, simulation, hypothesis testing, AR-order selection,
and forecasting for univariate higher-order stochastic volatility SV(p)
models. Supports Gaussian, Student-t, and Generalized Error Distribution
(GED) innovations, with optional leverage effects. Estimation uses
closed-form Winsorized ARMA-SV (W-ARMA-SV) moment-based methods that
avoid numerical optimization. Hypothesis testing includes Local Monte
Carlo (LMC) and Maximized Monte Carlo (MMC) procedures for leverage
effects, heavy tails, and autoregressive order. AR-order selection is
also available via information criteria (BIC/AIC) using the Kalman-filter
quasi-likelihood and the Hannan-Rissanen ARMA residual variance.
Forecasting is based on Kalman filtering and smoothing. See Ahsan and
Dufour (2021) <doi:10.1016/j.jeconom.2021.03.008>, Ahsan, Dufour, and
Rodriguez-Rondon (2025) <doi:10.1111/jtsa.12851>, and Ahsan, Dufour, and
Rodriguez-Rondon (2026) <doi:10.34989/swp-2026-8> for details.
| Version: |
0.2.0 |
| Imports: |
Rcpp (≥ 1.0.0), gsignal, stats |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
pso, GenSA, testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: |
2026-05-15 |
| DOI: |
10.32614/CRAN.package.wARMASVp |
| Author: |
Gabriel Rodriguez-Rondon
 [aut, cre],
Md. Nazmul Ahsan [aut],
Jean-Marie Dufour [aut] |
| Maintainer: |
Gabriel Rodriguez-Rondon <gabriel.rodriguezrondon at mail.mcgill.ca> |
| BugReports: |
https://github.com/roga11/wARMASVp/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/roga11/wARMASVp |
| NeedsCompilation: |
yes |
| Citation: |
wARMASVp citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
wARMASVp results |
Documentation:
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