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ArvindSt is an R package implementing the Arvind distribution and five novel stochastic regression models with Arvind-distributed errors.
Install the development version from GitHub:
# install.packages("devtools")
devtools::install_github("shikhartyagi/ArvindSt")darvind(),
parvind(), qarvind(), rarvind(),
rarvind_centred()fit_rw1() — Random Walk on Coefficientsfit_tvlm() — Time-Varying Coefficient Linear Modelfit_simex() — Simulation-Extrapolationfit_mixed() — Mixed-Effects Regressionfit_hmm() — Regime-Switching (HMM)diagnostics_arvind() (21
metrics), plot_arvind() (25 plots)forecast_arvind() with
Monte Carlo prediction intervalscv_arvind() (k-fold
and rolling-window)summary_arvind()library(ArvindSt)
# Load example data
data(climate_consumption)
# Define formula
frm <- Consumption ~ Precip + TempMaxAvg + TempMinAvg + HumidMax + HumidAvg
# Fit all five models
m1 <- fit_rw1(frm, climate_consumption)
m2 <- fit_tvlm(frm, climate_consumption)
m3 <- fit_simex(frm, climate_consumption, me_vars = c("Precip", "TempMaxAvg"))
m4 <- fit_mixed(frm, climate_consumption, group_var = "Season")
m5 <- fit_hmm(frm, climate_consumption, nstates = 2)
# Compare all models
summary_arvind(m1, m2, m3, m4, m5)MIT
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.