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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("remotes")
  remotes::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, drat 
#> nobs = 32, edf = 25.6, cll = -51.94, caic = 155.08, cbic = 192.61

summary(fit)
#>    var       edf         cll       caic       cbic      p_value
#> 1  mpg  0.000000 -100.189867 200.379733 200.379733           NA
#> 2 disp 13.187762   29.521786 -32.668047 -13.338271 9.065782e-08
#> 3 qsec  2.272103    4.454079  -4.363952  -1.033648 1.559593e-02
#> 4   hp  7.178554   10.836467  -7.315826   3.206038 3.267907e-03
#> 5 drat  2.965553    3.441702  -0.952298   3.394419 7.382604e-02

# 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 22.58394 22.45433
#> 2 22.53425 22.41825
#> 3 25.10289 24.93384
#> 4 20.70358 20.80241

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.

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.