ArvindSt: Five Novel Stochastic Regression Models with Arvind-Distributed Errors and Effects

Implements the 'Arvind' distribution and five novel stochastic regression models that replace the traditional Gaussian error assumption with 'Arvind'-distributed errors. The 'Arvind' distribution is a flexible single-parameter continuous distribution on the positive real line characterised by a polynomial numerator with Gaussian-type decay. The package provides complete distribution functions (darvind(), parvind(), qarvind(), rarvind()), maximum likelihood estimation via fit_arvind_mle(), and five model-fitting routines: Random Walk on Coefficients via fit_rw1(), Time-Varying Coefficient Linear Model via fit_tvlm(), Simulation-Extrapolation via fit_simex(), Mixed-Effects Regression via fit_mixed(), and Regime-Switching Hidden Markov Model via fit_hmm(). Additionally provides Monte Carlo forecasting with prediction intervals via forecast_arvind(), comprehensive goodness-of-fit diagnostics (21 metrics and 25 plots) via diagnostics_arvind() and plot_arvind(), k-fold and rolling-window cross-validation via cv_arvind(), and unified model comparison via summary_arvind(). For more details see Pandey, Singh, Tyagi, and Tyagi (2024) "Modelling climate, COVID-19, and reliability data: A new continuous lifetime model under different methods of estimation", Statistics and Applications, 22(2), <https://ssca.org.in/journal.html>.

Version:	1.0.0
Depends:	R (≥ 4.0.0)
Imports:	stats, graphics, grDevices, utils, ggplot2, forecast, tvReg, lme4, depmixS4, reshape2, rlang
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2026-05-11
DOI:	10.32614/CRAN.package.ArvindSt
Author:	Shikhar Tyagi [aut, cre], Arvind Pandey [aut]
Maintainer:	Shikhar Tyagi <shikhar1093tyagi at gmail.com>
License:	MIT + file LICENSE
NeedsCompilation:	no
Language:	en-US
Materials:	README
CRAN checks:	ArvindSt results

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