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Variance

Source: R/api.R
nv_var.Rd

Computes the variance along the specified axes.

Usage

nv_var(x, axes = NULL, drop = TRUE, correction = 1L, nan_rm = FALSE)

Arguments

x

(arrayish)
Input array.

axes

(integer() | NULL)
Axes to reduce. Negative values count from the end, i.e. -1 refers to the last axis. If NULL (default), reduces over all axes, returning a scalar.

drop

(logical(1))
Whether to drop reduced axes.

correction

(integer(1))
Degrees of freedom correction. Default is 1 (Bessel's correction).

nan_rm

(logical(1))
How to handle NaN values in floating-point inputs. If FALSE (default), NaN propagates. If TRUE, NaN values are skipped.

Value

arrayish
Has the same data type as the input. When drop = TRUE, the reduced axes are removed. When drop = FALSE, the reduced axes are set to 1.

Details

Uses Bessel's correction by default (correction = 1), matching R's var(). Set correction = 0 for population variance.

See also

nv_sd(), nv_mean()

Examples

x <- nv_array(c(1, 2, 3, 4, 5))
nv_var(x)             # all axes -> scalar
#> AnvlArray
#>  2.5000
#> [ CPUf32{} ] 
nv_var(x, axes = 1L)
#> AnvlArray
#>  2.5000
#> [ CPUf32{} ] 
nv_var(nv_array(c(1, NaN, 3, 5)), axes = 1L, nan_rm = TRUE)
#> AnvlArray
#>  4
#> [ CPUf32{} ]