Description Usage Arguments Value Examples

Residual-based diagnostic plots for cumulative link and general
regression models using `ggplot`

graphics.

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## S3 method for class 'resid'
autoplot(
object,
output = c("qq", "fitted", "covariate"),
x = NULL,
fit = NULL,
distribution = qnorm,
ncol = NULL,
alpha = 1,
xlab = NULL,
color = "#444444",
shape = 19,
size = 2,
qqpoint.color = "#444444",
qqpoint.shape = 19,
qqpoint.size = 2,
qqline.color = "#888888",
qqline.linetype = "dashed",
qqline.size = 1,
smooth = TRUE,
smooth.color = "red",
smooth.linetype = 1,
smooth.size = 1,
fill = NULL,
resp_name = NULL,
...
)
## S3 method for class 'glm'
autoplot(
object,
output = c("qq", "fitted", "covariate"),
x = NULL,
fit = NULL,
distribution = qnorm,
ncol = NULL,
alpha = 1,
xlab = NULL,
color = "#444444",
shape = 19,
size = 2,
qqpoint.color = "#444444",
qqpoint.shape = 19,
qqpoint.size = 2,
qqline.color = "#888888",
qqline.linetype = "dashed",
qqline.size = 1,
smooth = TRUE,
smooth.color = "red",
smooth.linetype = 1,
smooth.size = 1,
fill = NULL,
resp_name = NULL,
...
)
## S3 method for class 'clm'
autoplot(
object,
output = c("qq", "fitted", "covariate"),
x = NULL,
fit = NULL,
distribution = qnorm,
ncol = NULL,
alpha = 1,
xlab = NULL,
color = "#444444",
shape = 19,
size = 2,
qqpoint.color = "#444444",
qqpoint.shape = 19,
qqpoint.size = 2,
qqline.color = "#888888",
qqline.linetype = "dashed",
qqline.size = 1,
smooth = TRUE,
smooth.color = "red",
smooth.linetype = 1,
smooth.size = 1,
fill = NULL,
resp_name = NULL,
...
)
## S3 method for class 'lrm'
autoplot(
object,
output = c("qq", "fitted", "covariate"),
x = NULL,
fit = NULL,
distribution = qnorm,
ncol = NULL,
alpha = 1,
xlab = NULL,
color = "#444444",
shape = 19,
size = 2,
qqpoint.color = "#444444",
qqpoint.shape = 19,
qqpoint.size = 2,
qqline.color = "#888888",
qqline.linetype = "dashed",
qqline.size = 1,
smooth = TRUE,
smooth.color = "red",
smooth.linetype = 1,
smooth.size = 1,
fill = NULL,
resp_name = NULL,
...
)
## S3 method for class 'orm'
autoplot(
object,
output = c("qq", "fitted", "covariate"),
x = NULL,
fit = NULL,
distribution = qnorm,
ncol = NULL,
alpha = 1,
xlab = NULL,
color = "#444444",
shape = 19,
size = 2,
qqpoint.color = "#444444",
qqpoint.shape = 19,
qqpoint.size = 2,
qqline.color = "#888888",
qqline.linetype = "dashed",
qqline.size = 1,
smooth = TRUE,
smooth.color = "red",
smooth.linetype = 1,
smooth.size = 1,
fill = NULL,
resp_name = NULL,
...
)
## S3 method for class 'polr'
autoplot(
object,
output = c("qq", "fitted", "covariate"),
x = NULL,
fit = NULL,
distribution = qnorm,
ncol = NULL,
alpha = 1,
xlab = NULL,
color = "#444444",
shape = 19,
size = 2,
qqpoint.color = "#444444",
qqpoint.shape = 19,
qqpoint.size = 2,
qqline.color = "#888888",
qqline.linetype = "dashed",
qqline.size = 1,
smooth = TRUE,
smooth.color = "red",
smooth.linetype = 1,
smooth.size = 1,
fill = NULL,
resp_name = NULL,
...
)
## S3 method for class 'vglm'
autoplot(
object,
output = c("qq", "fitted", "covariate"),
x = NULL,
fit = NULL,
distribution = qnorm,
ncol = NULL,
alpha = 1,
xlab = NULL,
color = "#444444",
shape = 19,
size = 2,
qqpoint.color = "#444444",
qqpoint.shape = 19,
qqpoint.size = 2,
qqline.color = "#888888",
qqline.linetype = "dashed",
qqline.size = 1,
smooth = TRUE,
smooth.color = "red",
smooth.linetype = 1,
smooth.size = 1,
fill = NULL,
resp_name = NULL,
...
)
``` |

`object` |
An object of class |

`output` |
Character string specifying what to plot. Default is |

`x` |
A vector giving the covariate values to use for residual-by-
covariate plots (i.e., when |

`fit` |
The fitted model from which the residuals were extracted. (Only
required if |

`distribution` |
Function that computes the quantiles for the reference
distribution to use in the quantile-quantile plot. Default is |

`ncol` |
Integer specifying the number of columns to use for the plot
layout (if requesting multiple plots). Default is |

`alpha` |
A single values in the interval [0, 1] controlling the opacity
alpha of the plotted points. Only used when |

`xlab` |
Character string giving the text to use for the x-axis label in
residual-by-covariate plots. Default is |

`color` |
Character string or integer specifying what color to use for the
points in the residual vs fitted value/covariate plot.
Default is |

`shape` |
Integer or single character specifying a symbol to be used for plotting the points in the residual vs fitted value/covariate plot. |

`size` |
Numeric value specifying the size to use for the points in the residual vs fitted value/covariate plot. |

`qqpoint.color` |
Character string or integer specifying what color to use for the points in the quantile-quantile plot. |

`qqpoint.shape` |
Integer or single character specifying a symbol to be used for plotting the points in the quantile-quantile plot. |

`qqpoint.size` |
Numeric value specifying the size to use for the points in the quantile-quantile plot. |

`qqline.color` |
Character string or integer specifying what color to use for the points in the quantile-quantile plot. |

`qqline.linetype` |
Integer or character string (e.g., |

`qqline.size` |
Numeric value specifying the thickness of the line in the quantile-quantile plot. |

`smooth` |
Logical indicating whether or not too add a nonparametric
smooth to certain plots. Default is |

`smooth.color` |
Character string or integer specifying what color to use for the nonparametric smooth. |

`smooth.linetype` |
Integer or character string (e.g., |

`smooth.size` |
Numeric value specifying the thickness of the line for the nonparametric smooth. |

`fill` |
Character string or integer specifying the color to use to fill
the boxplots for residual-by-covariate plots when |

`resp_name` |
Character string to specify the response name that will be displayed in the figure. |

`...` |
Additional optional arguments to be passed onto |

A `"ggplot"`

object.

A `"ggplot"`

object.

1 2 3 4 5 6 7 8 | ```
# Load data
data(df1)
# Fit cumulative link model
fit <- glm(y ~ x + I(x ^ 2), data = df1, family = binomial)
# Construct residual plots
p1 <- ggplot2::autoplot(fit, jitter.scale = "probability", output = "qq")
p2 <- ggplot2::autoplot(fit, output = "covariate", x = df1$x)
p3 <- ggplot2::autoplot(fit, output = "fitted")
``` |

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