Description Usage Arguments Value Examples
View source: R/variable_importance.R
variable_importance
measures importance of variables based on specified methods.
1 2 3 4 5 6 | variable_importance(
sample,
variables,
operation = "replicate_correlation",
...
)
|
sample |
tbl containing sample used to estimate parameters. |
variables |
character vector specifying observation variables. |
operation |
optional character string specifying method for computing variable importance. Currently, only |
... |
arguments passed to variable importance operation. |
data frame containing variable importance measures.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | set.seed(123)
x1 <- rnorm(10)
x2 <- x1 + rnorm(10) / 100
y1 <- rnorm(10)
y2 <- y1 + rnorm(10) / 10
z1 <- rnorm(10)
z2 <- z1 + rnorm(10) / 1
batch <- rep(rep(1:2, each = 5), 2)
treatment <- rep(1:10, 2)
replicate_id <- rep(1:2, each = 10)
sample <-
tibble::tibble(
x = c(x1, x2), y = c(y1, y2), z = c(z1, z2),
Metadata_treatment = treatment,
Metadata_replicate_id = replicate_id,
Metadata_batch = batch
)
head(sample)
# `replicate_correlation`` returns the median, min, and max
# replicate correlation (across batches) per variable
variable_importance(
sample = sample,
variables = c("x", "y", "z"),
operation = "replicate_correlation",
strata = c("Metadata_treatment"),
replicates = 2,
split_by = "Metadata_batch",
replicate_by = "Metadata_replicate_id",
cores = 1
)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.