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vinereg

R build status CRAN status

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

How to install

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 | wt, qsec, drat, gear 
#> nobs = 32, edf = 23.63, cll = -55.86, caic = 158.98, cbic = 193.62

summary(fit)
#>    var       edf         cll       caic        cbic      p_value
#> 1  mpg  0.000000 -100.135440 200.270879 200.2708794           NA
#> 2   wt 11.452248   28.706110 -34.507723 -17.7217520 4.161832e-08
#> 3 qsec  6.091637    7.596924  -3.010573   5.9181583 1.990142e-02
#> 4 drat  5.089693    5.742895  -1.306405   6.1537401 4.494112e-02
#> 5 gear  1.000000    2.232423  -2.464845  -0.9991094 3.459922e-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 23.38467 23.04676
#> 2 22.69125 22.36638
#> 3 26.29842 26.10553
#> 4 20.62143 20.63283

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.
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