Description Usage Arguments Details Value Examples

This function creates a list of indices for a stratified
nonparametric bootstrap. Corresponding to our Cluster
Omission Stability statistic implemented in
`clustomit`

, we omit each group in turn and
perform a stratified bootstrap without the group. We
denote the number of groups as `num_clusters`

, which
is equal to `nlevels(factor(y))`

. Specifically,
suppose that we omit the *k*th group. That is, we
ignore all of the observations corresponding to group
*k*. Then, we sample with replacement from each of
the remaining groups (i.e., every group except for group
*k*), yielding a set of bootstrap indices.

1 | ```
boot_stratified_omit(y, num_reps = 50)
``` |

`y` |
a vector that denotes the grouping of each
observation. It must be coercible with |

`num_reps` |
the number of bootstrap replications to use for each group |

The returned list contains *K \times num_reps*
elements.

named list containing indices for each bootstrap replication

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
set.seed(42)
# We use 4 clusters, each with up to 10 observations. The sample sizes are
# randomly chosen.
num_clusters <- 4
sample_sizes <- sample(10, num_clusters, replace = TRUE)
# Create the cluster labels, y.
y <- unlist(sapply(seq_len(num_clusters), function(k) {
rep(k, sample_sizes[k])
}))
# Use 20 reps per group.
boot_stratified_omit(y, num_reps = 20)
# Use the default number of reps per group.
boot_stratified_omit(y)
``` |

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