group_bootstraps | R Documentation |
Group bootstrapping creates splits of the data based on some grouping variable (which may have more than a single row associated with it). A common use of this kind of resampling is when you have repeated measures of the same subject. A bootstrap sample is a sample that is the same size as the original data set that is made using replacement. This results in analysis samples that have multiple replicates of some of the original rows of the data. The assessment set is defined as the rows of the original data that were not included in the bootstrap sample. This is often referred to as the "out-of-bag" (OOB) sample.
group_bootstraps(data, group, times = 25, apparent = FALSE, ...)
data |
A data frame. |
group |
A variable in |
times |
The number of bootstrap samples. |
apparent |
A logical. Should an extra resample be added where the
analysis and holdout subset are the entire data set. This is required for
some estimators used by the |
... |
Not currently used. |
The argument apparent
enables the option of an additional
"resample" where the analysis and assessment data sets are the same as the
original data set. This can be required for some types of analysis of the
bootstrap results.
An tibble with classes group_bootstraps
bootstraps
, rset
,
tbl_df
, tbl
, and data.frame
. The results include a column for the data
split objects and a column called id
that has a character string with the
resample identifier.
data(ames, package = "modeldata") set.seed(13) group_bootstraps(ames, Neighborhood, times = 3) group_bootstraps(ames, Neighborhood, times = 3, apparent = TRUE)
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