Perform stratified random sampling to balance outcomes
This function is used to perform stratified random sampling to balance outcomes among the shards.
stratrs(y, C=5, P=0)
y |
The binary/categorical/continuous outcome. |
C |
The number of shards to break the data set into. |
P |
For continuous data, we break the range into P segments via the quantiles. Specifying, P=20 seems to work reasonably well. |
To perform BART with large data sets, random sampling is employed
to break the data into C shards. Each shard should be
balanced with respect to the outcome. For binary/categorical
outcomes, stratified random sampling is employed with this function.
A vector is returned with each element assigned to a shard.
set.seed(12) x <- rbinom(25000, 1, 0.1) a <- stratrs(x) table(a, x) z <- pmin(rpois(25000, 0.8), 5) b <- stratrs(z) table(b, z)
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