fast_quantile: Compute quantiles

In ravetools: Signal and Image Processing Toolbox for Analyzing Intracranial Electroencephalography Data

Compute quantiles

Description

Compute quantiles

Usage

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, ...)

Arguments

x	numerical-value vector for fast_quantile and fast_median, and column-major matrix for fast_mvquantile and fast_mvmedian
prob	a probability with value from 0 to 1
na.rm	logical; if true, any NA are removed from x before the quantiles are computed
...	reserved for future use

Value

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).

Examples

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"
)

ravetools documentation built on Sept. 11, 2024, 9:06 p.m.