earth (version 0.1-2)

model.matrix.earth: Get the 'earth' basis matrix

Description

Get the basis matrix of an earth object.

Usage

## S3 method for class 'earth':
model.matrix(object, x, subset, which.terms, \dots)

Arguments

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 (but ignorin

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$which.terms.

...

Unused, but provided for generic/method consistency.

Value

• A bx matrix 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 basis matrix bx can be used, for example, as the input matrix to lm, as shown in the example below.

See Also

earth, get.nterms.per.degree, get.nused.preds.per.subset

Examples

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)
#    
#    Expression:
#      23.20824 
#      +  5.745962 * pmax(0,  Girth -   12.9) 
#      -  2.866452 * pmax(0,   12.9 -  Girth) 
#      + 0.7183364 * pmax(0, Height -     76) 
#    
#    Number of cases: 31
#    Selected 4 of 5 terms, and 2 of 2 predictors
#    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 p values are not meaningful
# yields:
#    Call:
#    lm(formula = trees$Volume ~ bx[, -1])
#
#    Residuals:
#         Min       1Q   Median       3Q      Max
#    -5.28999 -1.97818  0.07124  1.92087  4.12673
#
#    Coefficients:
#                          Estimate Std. Error t value Pr(>|t|)
#    (Intercept)            23.2082     0.9968  23.283  < 2e-16
#    bx[, -1]h(Girth-12.9)   5.7460     0.2969  19.352  < 2e-16
#    bx[, -1]h(12.9-Girth)  -2.8665     0.4443  -6.452 6.48e-07
#    bx[, -1]h(Height-76)    0.7183     0.1750   4.105 0.000335
#
#    Residual standard error: 2.812 on 27 degrees of freedom
#    Multiple R-Squared: 0.9737,        Adjusted R-squared: 0.9707
#    F-statistic: 332.8 on 3 and 27 DF,  p-value: < 2.2e-16

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