An implementation of the surrogate approach to residuals and
diagnostics for ordinal and general regression models; for details, see Liu
and Zhang (2017)
An R package for constructing SUrrogate-based REsiduals and diagnostics for ordinal and general regression models; based on the approach described in Dungang and Zhang (2017).
The sure
package is currently listed on CRAN and can easily be installed:
# Install from CRAN (recommended)install.packages("sure") # Alternatively, install the development version from GitHubif (!requireNamespace("devtools")) install.packages("devtools")devtools::install_github("AFIT-R/sure")
Liu, Dungang and Zhang, Heping. 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
surrogate
for returning the surrogate response values used in calculating the surrogate-based residuals. The surrogate response values can be useful for checking the proportionality assumption of fitted cumulative link models, among other things.MASS
, ordinal
, rms
, and VGAM
(#18).VGAM
package (i.e., objects of class "vgam"
).df4
and df5
for illustrating various uses of the surrogate residual for diagnostics an ordinal regression models.