| model.matrix.earth {earth} | R Documentation |
Get the basis matrix of an earth object.
## S3 method for class 'earth':
model.matrix(object = stop("no 'object' arg"),
x = NULL, subset = NULL, which.terms = NULL,
...,
env = parent.frame(),
trace = 0,
Callers.name = "model.matrix.earth")
object |
An earth object.
This is the only required argument.
|
x |
An input matrix with the same number of columns as the x matrix
used to construct the original earth object.
Default is NULL, meaning use the original x matrix after
taking the original subset, if any.
|
subset |
Which rows to use in x.
Default is NULL, meaning use all of x.
|
which.terms |
Which terms to use.
Default is NULL, meaning use object$selected.terms.
|
... |
Unused, but provided for generic/method consistency. |
env |
For internal use. |
trace |
Default 0. Set to non-zero to see which data model.matrix.earth is using.
|
Callers.name |
For internal use (used by earth in trace messages). |
A basis matrix bx of the same form returned by earth.
If x, subset, and which.terms are all NULL, this
function returns the object's bx. In this case, it is perhaps easier
to simply use object$bx.
The format of bx is described in earth.
The matrix bx can be used
as the input matrix to lm or glm,
as shown below in the example.
In fact, that is what earth does internally after the pruning pass —
it calls lm.fit,
and additionally glm if earth's glm argument is used.
data(trees)
a <- earth(Volume ~ ., data = trees)
summary(a, decomp = "none") # "none" to print terms in same seq as a.lm below
# yields:
# Call: earth(formula = Volume ~ ., data = trees)
#
# Volume
# (Intercept) 23.208
# h(Girth-12.9) 5.746
# h(12.9-Girth) -2.866
# h(Height-76) 0.718
#
# Selected 4 of 5 terms, and 2 of 2 predictors
# Estimated importance: Girth Height
# Number of terms at each degree of interaction: 1 3 (additive model)
# GCV 11.48697 RSS 213.4354 GRSq 0.958859 RSq 0.9736697
bx <- model.matrix(a) # equivalent to bx <- a$bx
a.lm <- lm(trees$Volume ~ bx[,-1]) # -1 to drop intercept
summary(a.lm) # yields same coeffs as above summary
# displayed t values are not meaningful
# yields:
# Call:
# lm(formula = trees$Volume ~ bx[, -1])
#
# Residuals:
# Min 1Q Median 3Q Max
# -5.2900 -1.9782 0.0712 1.9209 4.1267
#
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) 23.208 0.997 23.28 < 2e-16
# bx[, -1]h(Girth-12.9) 5.746 0.297 19.35 < 2e-16
# bx[, -1]h(12.9-Girth) -2.866 0.444 -6.45 6.5e-07
# bx[, -1]h(Height-76) 0.718 0.175 4.10 0.00034
#
# Residual standard error: 2.81 on 27 degrees of freedom
# Multiple R-squared: 0.974, Adjusted R-squared: 0.971
# F-statistic: 333 on 3 and 27 DF, p-value: <2e-16