Extract term names from a fitted model object.
xNam(mod, intercept = TRUE, aliased = TRUE, list = FALSE, env = NULL)A fitted model object, or a list or nested list of such objects.
Logical, whether the intercept should be included.
Logical, whether names of aliased terms should be included (see Details).
Logical, whether names should be returned as a list, with all multi-coefficient terms grouped under their main term names.
Environment in which to look for model data (used to construct the
model frame). Defaults to the formula() environment.
A character vector or list/nested list of term names.
Extract term names from a fitted model. Names of terms for which
coefficients cannot be estimated are also included if aliased = TRUE
(default). These may be terms which are perfectly correlated with other
terms in the model, so that the model design matrix is rank deficient.
# Term names from Shipley SEM
m <- shipley.sem
xNam(m)
#> $DD
#> [1] "(Intercept)" "lat"
#>
#> $Date
#> [1] "(Intercept)" "DD"
#>
#> $Growth
#> [1] "(Intercept)" "Date"
#>
#> $Live
#> [1] "(Intercept)" "Growth"
#>
xNam(m, intercept = FALSE)
#> $DD
#> [1] "lat"
#>
#> $Date
#> [1] "DD"
#>
#> $Growth
#> [1] "Date"
#>
#> $Live
#> [1] "Growth"
#>
# Model with different types of predictor (some multi-coefficient terms)
d <- data.frame(
y = rnorm(100),
x1 = rnorm(100),
x2 = as.factor(rep(c("a", "b", "c", "d"), each = 25)),
x3 = rep(1, 100)
)
m <- lm(y ~ poly(x1, 2) + x2 + x3, data = d)
xNam(m)
#> [1] "(Intercept)" "poly(x1, 2)1" "poly(x1, 2)2" "x2b" "x2c"
#> [6] "x2d" "x3"
xNam(m, aliased = FALSE) # drop term that cannot be estimated (x3)
#> [1] "(Intercept)" "poly(x1, 2)1" "poly(x1, 2)2" "x2b" "x2c"
#> [6] "x2d"
xNam(m, aliased = FALSE, list = TRUE) # names as list
#> $`(Intercept)`
#> [1] "(Intercept)"
#>
#> $`poly(x1, 2)`
#> [1] "poly(x1, 2)1" "poly(x1, 2)2"
#>
#> $x2
#> [1] "x2b" "x2c" "x2d"
#>