Produces two and three dimensional plots of the
fitted values from a polymars object.
# S3 method for polymars
plot(x, predictor1, response, predictor2, xx, add = FALSE, n,
xyz = FALSE, contour.polymars = FALSE, xlim, ylim, intercept, ...)polymars object, typically the result of polymars.
the index of a predictor that was used when the polymars model was fit.
For the two dimensional plots, this variable is plotted along the X-axis.
if the model was fitted to multiple response data the response index should be specified.
the index of a predictor that was used when the polymars model was fit. For the three
dimensional plots, this variable is plotted along the Y-axis.
See xyz.
should be a vector of length equal to the number of predictors in the
original data set. The values should be in the same order as in the original
dataset. By default the function uses the median values of the data that was
used to fit the model. Although the values for predictor and predictor2 are
not used, they should still be provided as part of xx.
should the plot be added to a previously created plot? Works only for two dimensional plots.
number of plotting points (2 dimensional plot) or plotting points along each
axis (3 dimensional plot). The default is n = 100 for 2 dimensional plots and
n = 33 for 3 dimensional plots.
is the plot being made a 3 dimensional plot?
If there is only one response it need not be set, if two numerical values
accompany the model in the call they will be understood as two predictors
for a 3-d plot. By default a 3-d plot uses the persp function.
Categorical predictors cannot be used for 3 dimensional plots.
if the plot being made a 3 dimensional plot should it be made as a contour plot
(TRUE) or a perspective plot (FALSE).
function contour is being made.
Setting intercept equal to FALSE evaluates the object without intercept. The
intercept may also be given any numerical value which overrides the fitted
coefficient from the object. The default is TRUE.
Plotting limits. The function tries to choose intelligent limits itself
other options are passed on.
This function produces a 2-d plot of 1 predictor and response of a polymars object
at n equally spaced points or a 3-d plot of two predictors and response of a
polymars object. The range of the plot is by default equal to the range of the
particular predictor(s) in the original data, but this can be changed by
xlim = c(from, to) and
ylim = c(from, to).
Charles Kooperberg, Smarajit Bose, and Charles J. Stone (1997). Polychotomous regression. Journal of the American Statistical Association, 92, 117--127.
Charles J. Stone, Mark Hansen, Charles Kooperberg, and Young K. Truong. The use of polynomial splines and their tensor products in extended linear modeling (with discussion) (1997). Annals of Statistics, 25, 1371--1470.
design.polymars,
polymars,
predict.polymars,
summary.polymars.
# NOT RUN {
data(state)
state.pm <- polymars(state.region, state.x77, knots = 15, classify = TRUE, gcv = 1)
plot(state.pm, 3, 4)
# }
Run the code above in your browser using DataCamp Workspace