Standard deviation and Euclidean distance (C backend)

core_sd() is the square root of the variance computed by the shared core; core_dist() is the Euclidean distance between two equal-length vectors.

Usage

core_sd(x, ddof = 1L)

core_dist(a, b)

Arguments

x, a, b

Numeric vectors (coerced with as.numeric()) .

ddof

Denominator degrees of freedom. The default 1 gives the sample standard deviation, matching stats::sd(); 0 gives the population figure.

Value

A length-1 numeric.

Details

NA/NaN propagate – there is no na.rm. Call stats::na.omit() first if you need NA handling.

See also

core_moments() for the mean, variance, skewness and kurtosis in a single pass.

Examples

# Sample standard deviation, matching stats::sd().
core_sd(c(2, 4, 4, 4, 5, 5, 7, 9))
#> [1] 2.13809
all.equal(core_sd(1:10), stats::sd(1:10))
#> [1] TRUE

# ddof = 0 divides by n instead of n - 1.
core_sd(1:10, ddof = 0)
#> [1] 2.872281
all.equal(core_sd(1:10, ddof = 0), sqrt(mean((1:10 - mean(1:10))^2)))
#> [1] TRUE

# Euclidean distance between two points.
core_dist(c(0, 0), c(3, 4))     # 5
#> [1] 5
core_dist(1:5, 1:5)             # 0 -- a point is zero from itself
#> [1] 0