plotd {earth} | R Documentation |
Draw a plot of the distribution of the predicted values for each class.
plotd(obj, hist = FALSE, type = "response", nresponse = NULL, dichot = FALSE, trace = FALSE, xlim = NULL, ylim = NULL, jitter = FALSE, main=NULL, xlab = "Predicted Value", ylab = if(hist) "Count" else "Density", lty = 1, col = c("grey70", 1, "lightblue", "brown", "pink", 2, 3, 4), fill = if(hist) col[1] else 0, breaks = "Sturges", labels = FALSE, kernel = "gaussian", adjust = 1, zero.line = FALSE, legend = TRUE, legend.names = NULL, legend.pos = NULL, legend.cex = .8, legend.bg = "white", legend.extra = FALSE, vline.col = 0, vline.thresh = .5, vline.lty = 1, vline.lwd = 1, err.thresh = vline.thresh, err.col = 0, err.border = 0, err.lwd = 1, xaxt = "s", yaxt = "s", xaxis.cex = 1, sd.thresh = 0.01, ...)
To start off, look at the arguments obj
, hist
, type
.
For predict methods with multiple column responses, see the nresponse
argument.
For factor responses with more than two levels, see the dichot
argument.
obj |
Model object. Typically a model which predicts a class or a class discriminant. |
hist |
FALSE (default) to call density internally.TRUE to call hist internally.
|
type |
Type parameter passed to predict .
Default is "response" .
See the predict method for your object for possible values;
for example see predict.glm or predict.earth .
Typically you would set hist=TRUE if type="class" .
|
nresponse |
Column index for predicted responses with multiple columns.
The default is NULL , meaning use all columns of the predicted response.
|
dichot |
Dichotimise the predicted response.
This argument is ignored except for models where the observed response
is a factor with more than two levels
and the predicted response is a numeric vector.
The default FALSE separates the response into a group for each factor.
With dichot=TRUE the response is separated into just two groups:
the first level of the factor versus the remaining levels.
|
trace |
Default FALSE .
Use TRUE or 1 to trace plotd —
useful to see how plotd
partitions the predicted response into classes.
Use 2 for a full dump of the internal matrices.
|
xlim |
Limits of the x axis.
The default NULL means determine these limits automatically,
else specify c(xmin,xmax) .
|
ylim |
Limits of the y axis.
The default NULL means determine these limits automatically,
else specify c(ymin,ymax) .
|
jitter |
Jitter the histograms or densities horizontally to minimize overplotting.
Default FALSE .
Specify TRUE to automatically calculate the jitter,
else specify a numeric jitter value.
|
main |
Main title. Values:"string" string"" no titleNULL (default) generate a title from the call.
|
xlab |
x axis label.
Default is "Predicted Value" .
|
ylab |
y axis label.
Default is if(hist) "Count" else "Density" .
|
lty |
Per class line types for the plotted lines. Default is 1 (which gets recycled for all lines). |
col |
Per class line colors. The first few colors of the default are intended to be easily distinguishable on both color displays and monochrome printers. |
fill |
Fill color for the plot for the first class.
For hist=FALSE , the default is 0, i.e., no fill.
For hist=TRUE , the default is the first element in the col argument.
|
breaks |
Passed to hist .
Only used if hist=TRUE .
Default is "Sturges" .
When type="class" , setting breaks to a low number
can be used to widen the histogram bars
|
labels |
TRUE to draw counts on the hist plot.
Only used if hist=TRUE .
Default is FALSE .
|
kernel |
Passed to density .
Only used if hist=FALSE .
Default is "gaussian" .
|
adjust |
Passed to density .
Only used if hist=FALSE .
Default is 1 .
|
zero.line |
Passed to plot.density .
Only used if hist=FALSE .
Default is FALSE .
|
legend |
TRUE (default) to draw a legend, else FALSE .
|
legend.names |
Class names in legend.
The default NULL means determine these automatically.
|
legend.pos |
Position of the legend.
The default NULL means position the legend automatically,
else specify c(x,y) .
|
legend.cex |
cex for legend .
Default is .8 .
|
legend.bg |
bg color for legend .
Default is "white" .
|
legend.extra |
Show (in the legend) the number of occurrences of each class.
Default is FALSE .
|
vline.thresh |
Horizontal position of optional vertical line.
Default is 0.5 .
The vertical line is intended to indicate class separation.
If you use this, don't forget to set vline.col .
|
vline.col |
Color of vertical line. Default is 0, meaning no vertical line. |
vline.lty |
Line type of vertical line.
Default is 1 .
|
vline.lwd |
Line width of vertical line.
Default is 1 .
|
err.thresh |
x axis value specifying the error shading threshold.
See err.col .
Default is vline.thresh .
|
err.col |
Specify up to three colors to shade the "error areas" of the density plot.
The default is 0 , meaning no error shading.
This argument is ignored unless hist=FALSE .
If there are more than two classes, err.col uses only the first two.
This argument is best explained by running an example:data(etitanic) earth.model <- earth(survived ~ ., data=etitanic) plotd(earth.model, vline.col=1, err.col=c(2,3,4))The three areas are (i) the error area to the left of the threshold, (ii) the error area to the right of the threshold, and, (iii) the reducible error area. If less than three values are specified, plotd re-uses values in a sensible manner.
Use values of 0 to skip areas.
Disjoint regions are not handled well by the current implementation.
|
err.border |
Borders around the error shading.
Default is 0 , meaning no borders, else specify up to three colors.
|
err.lwd |
Line widths of borders of the error shading.
Default is 1 , else specify up to three line widths.
|
xaxt |
Default is "s" .
Use xaxt="n" for no x axis.
|
yaxt |
Default is "s" .
Use yaxt="n" for no y axis.
|
xaxis.cex |
Only used if hist=TRUE and type="class" .
Specify size of class labels drawn on the x axis.
Default is 1.
|
sd.thresh |
Minimum acceptable standard deviation for a density.
Default is 0.01 .
Densities with a standard deviation less than sd.thresh
will not be plotted (a warning will be issued and the legend
will say "not plotted" ).
|
... |
Extra arguments passed to the predict method for the object. |
This function calls predict
with the data originally used to build
the model, and with the type
specified above.
It then separates the predicted values into classes,
where the class for each predicted value
is determined by the class of the observed response.
Finally, it calls density
(or hist
if hist=TRUE
) for each class-specific set of values,
and plots the results.
This function estimates distributions with the
density
and hist
functions,
and also calls plot.density
and plot.histogram
.
For an overview see Venables and Ripley MASS section 5.6.
Partitioning the response into classes
Considerable effort is made to partition the predicted response
into classes in a sensible way.
This is not always possible for multiple column responses and the nresponse
argument
should be used where necessary.
The partitioning details depend on the types and numbers of columns in the observed
and predicted responses.
These in turn depend on the model object and the type
argument.
Use the trace
argument to see how plotd
partitions the
response for your model.
Degenerate densities
A message such as
Warning: standard deviation of "male" density is 0, density is degenerate?
means that the density for that class will not be plotted
(the legend will say "not plotted"
).
Set sd.thresh=0
to get rid of this check,
but be aware that histograms (and sometimes x axis labels)
for degenerate densitites will be misleading.
Using plotd for various models
This function is included in the earth
package
but can also be used with other models.
Example with glm
:
library(earth); data(etitanic) glm.model <- glm(sex ~ ., data=etitanic, family=binomial) plotd(glm.model)Example with
lm
:library(earth); data(etitanic) lm.model <- lm(as.numeric(sex) ~ ., data=etitanic) plotd(lm.model)Using plotd with lda
The plotd
function has special handling for lda
objects.
For such objects, the type
argument can take one of the
following values:
"response"
(default) linear discriminant
"ld"
same as "response"
"class"
predicted classes
"posterior"
posterior probabilities
Example:
library(MASS); library(earth); data(etitanic) lda.model <- lda(sex ~ ., data=etitanic) plotd(lda.model) # linear discriminant by default plotd(lda.model, type="class", hist=TRUE, labels=TRUE)This handling of
type
is handled internally by plotd
and type
is not passed to predict.lda
(type
is used merely to select fields in the list
returned by predict.lda
).
The type names can be abbreviated down to a single character.
For objects created with lda.matrix
(as opposed to lda.formula
),
plotd
blindly assumes that the grouping
argument was the second argument.
plotd
does not yet support objects created with lda.data.frame
.
For lda
responses with more than two factor levels,
use the nresponse
argument to
select a column in the predicted response.
Thus with the default type="response"
,
use nresponse=1
to select just the first linear discriminant.
The default nresponse=NULL
selects all columns,
which is typically not what you want for lda
models.
Example:
library(MASS); library(earth); set.seed(1) # optional, for reproducibility example(lda) # creates a model called "z" plot(z, dimen=1) # invokes plot.lda from the MASS package plotd(z, nresponse=1, hist=1) # equivalent using plotd # nresponse=1 selects first linear discr.The
dichot=TRUE
argument is also useful for lda
responses with more than two factor levels.
TODO
Handle degenerate densities in a more useful way.
Add freq
argument for hist
.
density
, plot.density
hist
, plot.histogram
earth
, plot.earth
, plotmo
old.par <- par(no.readonly=TRUE); par(mfrow=c(2,2)); par(mar=c(4, 3, 1.7, 0.5)); par(mgp=c(1.6, 0.6, 0)); par(cex = 0.8) data(etitanic) fit <- earth(survived ~ ., data=etitanic, degree=2, glm=list(family=binomial)) plotd(fit) plotd(fit, hist=TRUE, legend.pos=c(.25,220)) plotd(fit, hist=TRUE, type="class", labels=TRUE, xlab="", xaxis.cex=.8) par(old.par)