Description Usage Arguments Details
There are three types of plots that are currently written in the package:
plot_fitted
Plot the fitted regression line with credibility bands.
plot_predict
Plot residuals against fitted values.
plot_iter
Plot the progression of the log-likelihood value over time.
The S3 method plot
for class ipriorMod
currently returns plot_fitted
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ## S3 method for class 'ipriorMod'
plot(x, ...)
plot_resid(x)
plot_fitted_multilevel(x, X.var = 1, grp.var = 1, facet = c(2, 3),
cred.bands = TRUE, show.legend = TRUE, show.points = TRUE,
x.lab = NULL, y.lab = NULL, grp.lab = NULL, extrapolate = FALSE)
plot_fitted(x, X.var = 1, cred.bands = TRUE, size = 1,
linetype = "solid")
plot_iter(x, niter.plot = NULL, lab.pos = c("up", "down"))
plot_ppc(x, draws = 100)
|
x |
An |
... |
Not used |
X.var |
The index of the X variable to plot. |
grp.var |
Index of the grouping variable for multilevel plots. |
facet |
The index of the X variable in which to facet. This is a vector of maximum length 2. |
cred.bands |
Logical. Plot the confidence intervals? Defaults to
|
show.legend |
Logical. Show legend? |
show.points |
Logical. Show data points? |
x.lab |
(Optional) X axis label. |
y.lab |
(Optional) Y axis label. |
grp.lab |
(Optional) The name for the groups, which is also the legend title. |
extrapolate |
Logical. Extend the fitted regression line to fill the plot? |
size |
Size of the fitted line |
linetype |
Type of the fitted line |
niter.plot |
(Optional) Vector of length at most two, indicating the start and end points of the iterations to plot. |
lab.pos |
Adjust the position of the log-likelihood label. |
draws |
Number of draws for posterior predictive check. |
grp |
The index of the groups. |
See ggplot2 documentation for the plotting parameters.
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