plotmo {earth} | R Documentation |
Plot the predicted model response when varying one or two predictors while holding all the other predictors constant.
plotmo(object = stop("no 'object' arg"), degree1 = TRUE, degree2 = TRUE, ycolumn = 1, type="response", caption = if(do.par) NULL else "", ylim = NULL, clip = TRUE, inverse.func = NULL, col.response = 0, pch.response = 1, trace = FALSE, grid.func = median, grid.levels = NULL, ndegree1 = 500, lty.degree1 = 1, col.degree1 = 1, se = 0, col.shade = "lightblue", col.se = 0, lty.se = 2, func = NULL, col.func = "pink", pch.func = 20, nrug = 0, type2 = "persp", ngrid = 20, col.persp = "lightblue", col.image = grey(0:9/10), do.par = TRUE, main = NULL, theta = NA, phi = 30, shade = 0.5, ticktype = "simple", xlab = "", ylab = "", cex = NULL, ...)
To start off, look at the arguments
object
,
degree1
,
degree2
,
ylim
,
clip
, and
do.par
.
You will also need the ycolumn
argument if your model has multiple responses.
object |
Model object. This is the only required argument. |
degree1 |
Index vector specifying main effect plots to include.
Default is TRUE , meaning all.
Perhaps the easiest way to use this argument (and degree2 ) is to
first plot all figures to see how the figures are numbered, then
replot, using degree1 to select the figures you want.
|
degree2 |
Index vector specifying interaction plots to include.
Default is TRUE , meaning all.
|
ycolumn |
Specify which column of the response to plot if the model has multiple responses. Default is 1. |
type |
type parameter passed onto predict .
Default is "response" .
See predict.earth for other values for earth models.
|
caption |
Overall caption. The default value is
if(do.par) NULL else "" . Values are:"string" string"" no captionNULL generate a caption from object$call and the response name.
|
trace |
Set to TRUE to trace operation.
Useful for tracking down error messages.
Default is FALSE .
|
ylim |
Values are:NULL (default) all y axes have same limits
(where "y" is actually "z" on degree2 plots).
The limits are the min and max values of y across all (degree1 and degree2) plots.
If col.response!=0 then the original response is
also included in the min and max calculation.NA each graph has its own y limits.c(ymin,ymax) all graphs have the specified y limits. |
clip |
Plot only values that are in the range of the response of the original data.
Default is TRUE .
|
inverse.func |
Function applied to the predicted response before plotting.
Default is NULL , meaning do not apply a function.
For example, you could use inverse.func=exp if your
model formula is log(y)~x .
Note, however, that is usually unnecessary
to use inverse.func for models such as glm
with family=binomial , because the plotted response is already a probability.
|
col.response |
Color of response values (actually, the response sites in degree2 plots).
Here "response" refers to the original data used to build the model.
Default is 0, meaning don't plot the response.
Ignored by persp plots.
|
pch.response |
Plot character for col.response .
Default is 1.
|
grid.func |
Function applied to x columns to calculate the values for numeric predictors
not on the axes.
(For factor predictors, see the grid.levels argument below.)
Default is median .
Examples:
plotmo(a, grid.func = mean) # mean instead of median grid.func <- function(x) quantile(x)[2] # 25% quantile plotmo(a, grid.func = grid.func) |
grid.levels |
This argument only applies if model x-matrix has factors.
It has the same purpose as the grid.func argument above but applies to
factor predictors, not numeric predictors.
It is a list specifying which factor level to use for factor predictors
not on the axes. If specified, plotmo will print messages reminding you of how the levels are set.
Default is NULL meaning use the first level of each factor.
a <- earth(survived ~ pclass+sex+age, data=etitanic, degree=2) plotmo(a, degree2=0, grid.levels=list(pclass="2nd", sex="male"))The following arguments are for degree1 (main effect) plots |
ndegree1 |
Maximum number of points in each degree1 plot.
Default is 500 .
Special value -1 means use nrow(x) .
|
lty.degree1 |
Line type of degree 1 plots. Default is 1 .
|
col.degree1 |
Color of degree 1 plots. Default is 1 .
|
nrug |
Number of points in (jittered) rug.
Default is 0 meaning no rug.
Special value -1 for all, i.e., nrow(x) .
|
se |
Draw standard error bands at plus and minus se times the pointwise standard errors.
Default is 0 , meaning no standard error bands.
A common value is 2 .
The predict method for object must be callable with se.fit=TRUE
(examples are predict.lm but not predict.earth ).
|
col.shade |
Color of se shading. Default is "lightblue" .
Set to 0 for no shading.
|
col.se |
Color of se lines. Default is 0 meaning no lines just shading.
|
lty.se |
Line type of se lines. Default is 2 .
|
func |
Superimpose func(x) if func is not NULL .
Default is NULL .
This is useful if you are comparing the model to a known function.
Note that func is called with a single argument which
is a dataframe with columns in the same order as the predictors
in the formula or x used to build the model.
Set trace=TRUE to see the column names and first few rows of this dataframe.
|
col.func |
Color of func points.
Default is "pink" .
|
pch.func |
Plot character for func points.
Default is 20.The following arguments are for degree2 plots |
type2 |
Degree2 plot type.
One of "persp" (default), "contour" , or "image" .
|
col.persp |
Color of persp surface. Default is "lightblue" .
Set to 0 for no color.
|
col.image |
Colors of image plot. Default is grey(0:9/10) .
The default excludes grey(1) because that is the "color" of clipped
values, see clip .
|
ngrid |
Grid side length for degree2 plots. Default is 20 .The following settings are related to par() and are included so you can override the defaults.
|
do.par |
Call par() for global settings as appropriate.
Default is TRUE .
Set to FALSE if you want to append figures to an existing plot.
|
main |
Title of each plot.
Default is NULL , meaning generate figure headings automatically.
|
theta |
Rotation argument for persp .
Default is NA , meaning automatically rotate each graph so the highest corner is furthest away.
Use theta=-45 for x and y increasing as you move into the paper.
|
phi |
Phi argument for persp . Default is 30 .
|
shade |
Shade arg for persp . Default is 0.5 .
|
ticktype |
Ticks on persp plot. One of simple or detailed .
Default is "simple" .
|
xlab |
Horizontal axis label on degree1 plots
(for degree2 plots the abscissa labels are always the predictor names).
Default is "" , meaning none, which gives more plottable area.
Set to NULL to use the predictor names as labels.
If you use NULL , you may want to set main="" to avoid
redundant labeling.
|
ylab |
Vertical axis label.
Default is "" , meaning none, which gives more plottable area.
|
cex |
Character expansion. |
... |
Extra arguments passed to plotting functions called by plotmo .
Using arguments here may cause warnings which can often be safely ignored.
|
Plotmo
is a general purpose model plotting function
(but comes with the earth
package).
It is intended for models with quantitative responses.
The general idea
Plotmo plots a degree1 plot of predicted values by changing one predictor while holding all other predictors at a constant value. For degree2 plots, plotmo changes two variables while holding all other predictors at a constant value.
The question arises: what should the constant be for each predictor?
For numerical predictors it is the median of the predictor values in the input matrix x;
for factor predictors it is the first level of the factor.
You can change those defaults with the grid.func
and grid.levels
arguments.
Each graph shows only a thin slice of the data because most variables are fixed. You should be aware of that when interpreting the graph.
Details of operation
Let's say the model object
has three predictors,
x1
, x2
, and x3
(all numeric)
and plotmo
is about to plot the degree1 plot for x2
.
Plotmo
first builds an input matrix
with ndegree1
rows and with column names x1
, x2
, and x3
.
It sets all entries for the x1
column to x1
's median value (actually,
the value returned by grid.func
applied to x1
).
Likewise for the x3
column.
It sets the x2
column to an equally spaced sequence of values
from min(x2)
to max(x2)
.
Finally, it calls predict
(type=type)
with the newly created input matrix,
and plots the predicted values against the sequence of x2
values.
Operation is similar for degree2 plots: all columns of the input
matrix for predict
are set to their medians except for the columns of the two
predictors being plotted.
Note that by default plotmo
calls predict
with new data and
type="response"
, whereas termplot
calls predict
with type="terms"
.
Limitations
NAs are not allowed.
To prevent confusing error messages from plotmo
,
remove NAs before building your model.
(To be safe, you can use na.action=na.fail
when building your model
so you get an error message if you inadvertently have a NA.)
Weights are currently ignored, with a warning.
Factor predictors are not supported on degree2 graphs (you will get a reminder message).
To avoid confusing error messages from plotmo,
keep the original formula you used to build the model simple.
By default (i.e., when using get.plotmo.x.default
and get.pairs.default
),
plotmo
parses the input formula
using gsub
.
This crude approach is not infallible but works for the common formulas.
It determines which predictors are paired by looking for
forms such as "x1:x2"
or "x1*x2"
in the model formula.
Variable names containing $ are not supported.
The work around is to build the model using temporary variables
or to use attach
.
Plotmo
can get confused by predictors in formulas which use indexing, such as x[,3]
.
The symptom is usually a message along the lines
Error in model.frame: invalid type (list) for variable 'x[,3]'
.
A mesage like
Warning in model.frame.default: 'newdata' had 50 rows but variable(s) found have 31 rows
means that model.frame.default
cannot find all the variables in the data frame
created by plotmo
.
Minimum Requirements
Plotmo
requires the following of the model object.
These requirements are for default operation, which can be changed
as described in the next section.
1) object
must have a predict
method that supports type=response
.
2) object
must have the following two components
(which are searched for in the order given for each):
$x
, or $call$formula
(formula
is required for degree2 plots),
or $call$x
.
$y
, or $call$formula
, or $call$y
.
3) for optional standard error bands (see the se
argument),
object
must have a predict
method that can be called with se.fit=TRUE
.
Extending plotmo
Plotmo
calls the following generic functions, all defined in
the file plotmo.R
:
plotmo.prolog
get.plotmo.x
get.plotmo.y
plotmo.predict
get.singles
get.pairs
Thus plotmo
can be extended
by writing new method functions, although the default
functions may suffice for your object's class.
See the source comments for details.
FAQ
I want to add lines or points to a plot created by plotmo
.
and am having trouble getting my axis scaling right. Help?
Use do.par=FALSE
.
With do.par=FALSE
, the axis scales match the axis labels.
With do.par=TRUE
, plot.earth restores the
par
parameters and axis scales to
what they were before calling plot.earth.
This usually means that the x- and y-axis scales are both 0 to 1.
Stephen Milborrow. Users are encouraged to send feedback — use milboATsonicPERIODnet http://www.milbo.users.sonic.net.
termplot
,
plot.earth
,
plot.earth.models
,
plotd
data(ozone1) a <- earth(O3 ~ ., data = ozone1, degree = 2) plotmo(a) ## Not run: # example with some arguments plotmo(a, caption = "example", ylim = NULL, degree1 = c(1,2,4), degree2 = 4, col.response = 3, clip = FALSE, ticktype = "d", theta = -30) # examples using functions other than earth plotmo(lm(O3 ~ log(temp) + humidity*temp, data=ozone1), se=2) library(gam) data(airquality) airquality <- na.omit(airquality) # plotmo doesn't know how to deal with NAs plotmo(gam(Ozone^(1/3) ~ lo(Solar.R) + lo(Wind, Temp), data = airquality)) library(mgcv) plotmo(gam(O3 ~ s(doy) + s(humidity,temp), data=ozone1), se=2, ylim=NA) ## End(Not run)