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cff-version: 1.2.0
message: 'To cite package "varGuidTS" in publications use:'
type: software
license: MIT
title: 'varGuidTS: Variance-Guided Time-Series Modeling for Temporal Risk Detection'
version: 0.1.13
doi: 10.32614/CRAN.package.varGuidTS
abstract: Fits balanced-panel autoregressive models with conditional heteroscedasticity
  for temporal risk detection. The main estimator combines autoregressive exogenous
  mean modeling with GARCH-X variance modeling, subject-specific baseline terms, shared
  population coefficients, and L1 penalization for high-dimensional covariates. The
  package returns conditional mean and variance estimates, coefficient summaries,
  simulations, and exceedance-based risk scores defined as estimated conditional threshold-exceedance
  probabilities. The implementation builds on the lasso of Tibshirani (1996) <https://doi.org/10.1111/j.2517-6161.1996.tb02080.x>,
  generalized autoregressive conditional heteroscedasticity of Bollerslev (1986) <https://doi.org/10.1016/0304-4076(86)90063-1>,
  and L1-regularized high-dimensional time-series modeling of Medeiros and Mendes
  (2016) <https://doi.org/10.1016/j.jeconom.2015.10.011>.
authors:
- family-names: Wang
  given-names: Zihao
- family-names: Lu
  given-names: Min
  email: luminwin@gmail.com
repository: https://luminwin.r-universe.dev
repository-code: https://github.com/zionwzz/variance-guided-risk-demo
commit: ba159ccd2c7891bdbdd00b5a311687945df6c927
url: https://github.com/zionwzz/variance-guided-risk-demo
date-released: '2026-05-20'
contact:
- family-names: Lu
  given-names: Min
  email: luminwin@gmail.com