README.Rmd

---
output:
  md_document:
    variant: markdown_github
---

```{r setup, echo = FALSE}
knitr::opts_chunk$set(
  cache = TRUE,
  collapse = TRUE,
  comment = "#>",
  fig.align = "center",
  fig.path = "man/figures/README-"
)
```

# sure: Surrogate Residuals <img src="man/figures/sure-logo.png" align="right" width="130" height="150" />

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## Overview 

An R package for constructing **SU**rrogate-based **RE**siduals and diagnostics for ordinal and general regression models; based on the approach described in [Dungang and Zhang (2017)](http://www.tandfonline.com/doi/abs/10.1080/01621459.2017.1292915?journalCode=uasa20).


## Installation

The `sure` package is [currently listed on CRAN](https://CRAN.R-project.org/package=sure) and can easily be installed:
```r
# Install from CRAN (recommended)
install.packages("sure")
  
# Alternatively, install the development version from GitHub
if (!requireNamespace("devtools")) install.packages("devtools")
devtools::install_github("koalaverse/sure")
```


## References

Liu, D. and Zhang, H. Residuals and Diagnostics for Ordinal Regression Models: A Surrogate Approach.
*Journal of the American Statistical Association* (accepted). URL
http://www.tandfonline.com/doi/abs/10.1080/01621459.2017.1292915?journalCode=uasa20

Greenwell, B.M., McCarthy, A.J., Boehmke, B.C. & Dungang, L. (2018) "Residuals and diagnostics for binary and ordinal regression models: An introduction to the sure package." The R Journal (pre-print). URL https://journal.r-project.org/archive/2018/RJ-2018-004/index.html