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\docType{package}
\name{ArvindSt-package}
\alias{ArvindSt}
\alias{ArvindSt-package}
\title{ArvindSt: Five Novel Stochastic Regression Models with Arvind-Distributed Errors and Effects}
\description{
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).
}
\references{
Pandey, A., Singh, R.P., Tyagi, S., and Tyagi, A. (2024). Modelling climate, COVID-19, and reliability data: A new continuous lifetime model under different methods of estimation. \emph{Statistics and Applications}, 22(2).
}
\author{
\strong{Maintainer}: Shikhar Tyagi \email{shikhar1093tyagi@gmail.com} (\href{https://orcid.org/0000-0003-1606-0844}{ORCID})

Authors:
\itemize{
  \item Arvind Pandey \email{arvindmzu@gmail.com}
}

}
\keyword{internal}
