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 (may not be active yet) |
| 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 |
Documentation:
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