View source: R/fast_quantile.R
fast_quantile | R Documentation |
Compute quantiles
fast_quantile(x, prob = 0.5, na.rm = FALSE, ...)
fast_median(x, na.rm = FALSE, ...)
fast_mvquantile(x, prob = 0.5, na.rm = FALSE, ...)
fast_mvmedian(x, na.rm = FALSE, ...)
x |
numerical-value vector for |
prob |
a probability with value from 0 to 1 |
na.rm |
logical; if true, any |
... |
reserved for future use |
fast_quantile
and fast_median
calculate univariate
quantiles (single-value return); fast_mvquantile
and fast_mvmedian
calculate multivariate quantiles (for each column, result lengths equal to
the number of columns).
fast_quantile(runif(1000), 0.1)
fast_median(1:100)
x <- matrix(rnorm(100), ncol = 2)
fast_mvquantile(x, 0.2)
fast_mvmedian(x)
# Compare speed for vectors (usually 30% faster)
x <- rnorm(10000)
microbenchmark::microbenchmark(
fast_median = fast_median(x),
base_median = median(x),
# bioc_median = Biobase::rowMedians(matrix(x, nrow = 1)),
times = 100, unit = "milliseconds"
)
# Multivariate cases
# (5~7x faster than base R)
# (3~5x faster than Biobase rowMedians)
x <- matrix(rnorm(100000), ncol = 20)
microbenchmark::microbenchmark(
fast_median = fast_mvmedian(x),
base_median = apply(x, 2, median),
# bioc_median = Biobase::rowMedians(t(x)),
times = 10, unit = "milliseconds"
)
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