README.Rmd

---
output: md_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# vinereg
[![R build status](https://github.com/tnagler/vinereg/workflows/R-CMD-check/badge.svg)](https://github.com/tnagler/vinereg)
<!-- [![Coverage status](https://codecov.io/gh/tnagler/vinereg/branch/main/graph/badge.svg)](https://app.codecov.io/github/tnagler/vinereg?branch=main) -->
[![CRAN status](https://www.r-pkg.org/badges/version/vinereg)](https://cran.r-project.org/package=vinereg)

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

## How to install

- the stable release from CRAN:
     
    ``` r
    install.packages("vinereg")
    ```

- the latest development version:
    
    ``` r
    # install.packages("remotes")
    remotes::install_github("tnagler/vinereg", build_vignettes = TRUE)
    ```

## Functionality

See the [package website](https://tnagler.github.io/vinereg/).

## Example

```{r, warning=FALSE}
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))

summary(fit)

# show marginal effects for all selected variables
plot_effects(fit)

# predict mean and median
head(predict(fit, mtcars, alpha = c(NA, 0.5)), 4)
```


## Vignettes
For more examples, have a look at the vignettes with

``` r
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](https://www.sciencedirect.com/science/article/pii/S0167947316303073), 
[preprint](https://arxiv.org/abs/1510.04161)

Schallhorn, N., Kraus, D., Nagler, T., Czado, C. (2017). D-vine quantile 
regression with discrete variables. Working paper, 
[preprint](https://arxiv.org/abs/1705.08310).