README.md

In vinereg: D-Vine Quantile Regression

vinereg

An R package for D-vine copula based mean and quantile regression.

How to install

• the stable release from CRAN:

  install.packages("vinereg")
  

• the latest development version:

  # install.packages("devtools")
  devtools::install_github("tnagler/vinereg", build_vignettes = TRUE)
  

Functionality

See the package website.

Example

set.seed(5)
library(vinereg)
data(mtcars)

# declare factors and discrete variables
for (var in c("cyl", "vs", "gear", "carb"))
    mtcars[[var]] <- as.ordered(mtcars[[var]])
mtcars[["am"]] <- as.factor(mtcars[["am"]])

# fit model
(fit <- vinereg(mpg ~ ., family = "nonpar", data = mtcars))
#> D-vine regression model: mpg | disp, qsec, hp 
#> nobs = 32, edf = 21.86, cll = -55.94, caic = 155.59, cbic = 187.63

summary(fit)
#>    var       edf         cll       caic        cbic      p_value
#> 1  mpg  0.000000 -100.189867 200.379733 200.3797334           NA
#> 2 disp 11.177711   29.363521 -36.371618 -19.9880453 1.873313e-08
#> 3 qsec  2.328636    4.167727  -3.678182  -0.2650159 2.180106e-02
#> 4   hp  8.353178   10.723533  -4.740711   7.5028411 7.480400e-03

# show marginal effects for all selected variables
plot_effects(fit)
#> `geom_smooth()` using method = 'loess' and formula 'y ~ x'

# predict mean and median
head(predict(fit, mtcars, alpha = c(NA, 0.5)), 4)
#>       mean      0.5
#> 1 22.36600 22.27170
#> 2 22.18247 22.01755
#> 3 25.33357 24.90170
#> 4 20.24950 20.03959

Vignettes

For more examples, have a look at the vignettes with

vignette("abalone-example", package = "vinereg")
vignette("bike-rental", package = "vinereg")

References

Kraus and Czado (2017). D-vine copula based quantile regression. Computational Statistics & Data Analysis, 110, 1-18. link, preprint

Schallhorn, N., Kraus, D., Nagler, T., Czado, C. (2017). D-vine quantile regression with discrete variables. Working paper, preprint.

vinereg documentation built on March 23, 2022, 5:06 p.m.