Estimate variable importances in an `earth`

object

`evimp(object, trim=TRUE, sqrt.=TRUE)`

object

An `earth`

object.

trim

If `TRUE`

(default), delete rows in the returned matrix for
variables that don't appear in any subsets.

sqrt.

Default is `TRUE`

,
meaning take the `sqrt`

of the GCV and RSS importances before
normalizing to 0 to 100.
Taking the square root gives a better indication of
relative importances because the raw importances are calculated using
a sum of squares.
Use `FALSE`

to not take the square root.

This function returns a matrix showing the relative importances of the
variables in the model. There is a row for each variable. The row
name is the variable name, but with `-unused`

appended if the
variable does not appear in the final model.

The columns of the matrix are (not all of these are printed by `print.evimp`

):

`col`

: Column index of the variable in the`x`

argument to`earth`

.`used`

: 1 if the variable is used in the final model, else 0. Equivalently, 0 if the row name has an`-unused`

suffix.`nsubsets`

: Variable importance using the "number of subsets" criterion. Is the number of subsets that include the variable (see "Three Criteria" in the chapter on`evimp`

in the`earth`

vignette “Notes on the earth package”).`gcv`

: Variable importance using the GCV criterion (see "Three Criteria").`gcv.match`

: 1, except is 0 where the rank using the`gcv`

criterion differs from that using the`nsubsets`

criterion. In other words, there is a 0 for values that increase as you go down the`gcv`

column.`rss`

: Variable importance using the RSS criterion (see "Three Criteria").`rss.match`

: Like`gcv.match`

but for the`rss`

.

The rows are sorted on the `nsubsets`

criterion.
This means that values in the `nsubsets`

column decrease as you go down the column
(more accurately, they are non-increasing).
The values in the `gcv`

and `rss`

columns
are also non-increasing, except where the
`gcv`

or `rss`

rank differs from the `nsubsets`

ranking.

# NOT RUN { data(ozone1) earth.mod <- earth(O3 ~ ., data=ozone1, degree=2) ev <- evimp(earth.mod, trim=FALSE) plot(ev) print(ev) # }