Smooth Generalized Normal Distribution"

In smoothic: Variable Selection Using a Smooth Information Criterion

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

To begin, load the package.

library(smoothic)

Boston Housing Data

Perform automatic variable selection using a smooth information criterion.

fit <- smoothic(
  formula = lcmedv ~ .,
  data = bostonhouseprice2,
  family = "sgnd", # Smooth Generalized Normal Distribution
  model = "mpr" # model location and scale
)

Display the estimates and standard errors.

summary(fit)

fit$kappa # shape estimate

Plot the standardized coefficient values with respect to the epsilon-telescope.

plot_paths(fit)

Plot the model-based conditional density curves.

plot_effects(fit,
             what = c("ltax", "rm", "ldis"), # or "all" for all selected variables
             density_range = c(2.25, 3.75))

smoothic documentation built on Aug. 22, 2023, 5:07 p.m.