Data simulated from a probit model with heteroscedasticity. The data are
described in Example 4 of Liu and Zhang (2017).

datasets

An implementation of the surrogate approach to residuals and
diagnostics for ordinal and general regression models; for details, see Liu
and Zhang (2017) <doi:10.1080/01621459.2017.1292915>. These residuals can be
used to construct standard residual plots for model diagnostics (e.g.,
residual-vs-fitted value plots, residual-vs-covariate plots, Q-Q plots, etc.).
The package also provides an 'autoplot' function for producing standard
diagnostic plots using 'ggplot2' graphics. The package currently supports
cumulative link models from packages 'MASS', 'ordinal', 'rms', and 'VGAM'.
Support for binary regression models using the standard 'glm' function is also
available.

Brandon Greenwell

sure

Surrogate Residuals for Ordinal and General Regression Models

Andrew McCarthy

Brad Boehmke

Dungang Liu

df2 function

A data frame with 2000 rows and 2 variables.<ul>
<li><code>x</code> The predictor variable.</li>
<li><code>y</code> The response variable; an ordered factor.</li>
</ul>

df2: Simulated Heteroscedastic Data

Description

Usage

Arguments

Format

References

Examples