Description Usage Arguments Details Value Note Author(s)
These functions are provided for compatibility with older versions only, and may be defunct as soon as the next release.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | ## S3 method for class 'perry'
fortify(
model,
data,
select = NULL,
reps = model$splits$R > 1,
seFactor = NA,
...
)
## S3 method for class 'perrySelect'
fortify(
model,
data,
subset = NULL,
select = NULL,
reps = model$splits$R > 1,
seFactor = model$seFactor,
...
)
## S3 method for class 'perryTuning'
fortify(model, data, ...)
## Default S3 method:
perryPlot(
object,
method = c("box", "density", "dot", "line"),
mapping,
facets = attr(object, "facets"),
...
)
|
model |
an object inheriting from class |
data |
currently ignored. |
select |
a character, integer or logical vector indicating the columns of prediction error results to be converted. |
reps |
a logical indicating whether to convert the results from all
replications ( |
seFactor |
a numeric value giving the multiplication factor of the
standard error for displaying error bars in dot plots or line plots. Error
bars in those plots can be suppressed by setting this to |
... |
for the |
subset |
a character, integer or logical vector indicating the subset of models to be converted. |
object |
an object inheriting from class |
method |
a character string specifying the type of plot. Possible
values are |
mapping |
an aesthetic mapping to override the default behavior (see
|
facets |
a faceting formula to override the default behavior. If
supplied, |
The fortify methods extract all necessary information for plotting
from resampling-based prediction error results and store it in a data frame.
The default method of perryPlot creates the corresponding plot from
the data frame returned by fortify.
The fortify methods return a data frame containing the
columns listed below, as well as additional information stored in the
attribute "facets" (default faceting formula for the plots).
Fita vector or factor containing the identifiers of the models.
Namea factor containing the names of the predictor error results (not returned in case of only one column of prediction error results with the default name).
PEthe estimated prediction errors.
Lowerthe lower end points of the error bars (only returned
if reps is FALSE).
Upperthe upper end points of the error bars (only returned
if reps is FALSE).
Duplicate indices in subset or select are removed such
that all models and prediction error results are unique.
Andreas Alfons
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.