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Normal distribution functions

Source: R/stats.R
mlx_dnorm.Rd

Compute density (mlx_dnorm), cumulative distribution (mlx_pnorm), and quantile (mlx_qnorm) functions for the normal distribution using MLX.

Usage

mlx_dnorm(x, mean = 0, sd = 1, log = FALSE, device = mlx_default_device())

mlx_pnorm(x, mean = 0, sd = 1, device = mlx_default_device())

mlx_qnorm(p, mean = 0, sd = 1, device = mlx_default_device())

Arguments

x

Vector of quantiles (mlx array or coercible to mlx)

mean

Mean of the distribution (default: 0)

sd

Standard deviation of the distribution (default: 1)

log

If TRUE, return log density for mlx_dnorm (default: FALSE)

device

Execution target: supply "gpu", "cpu", or an mlx_stream created via mlx_new_stream(). Defaults to the current mlx_default_device() unless noted otherwise (helpers that act on an existing array typically reuse that array's device or stream).

p

Vector of probabilities (mlx array or coercible to mlx)

Value

An mlx array with the computed values.

See also

mlx_erf(), mlx_erfinv(), mlx.core.erf, mlx.core.erfinv

Examples

x <- as_mlx(seq(-3, 3, by = 0.5))
mlx_dnorm(x)
#> mlx array [13]
#>   dtype: float32
#>   device: gpu
#>   values:
#>  [1] 0.004431848 0.017528297 0.053990964 0.129517585 0.241970733 0.352065325
#>  [7] 0.398942292 0.352065325 0.241970733 0.129517585 0.053990964 0.017528297
#> [13] 0.004431848
mlx_pnorm(x)
#> mlx array [13]
#>   dtype: float32
#>   device: gpu
#>   values:
#>  [1] 0.001349896 0.006209671 0.022750139 0.066807210 0.158655256 0.308537543
#>  [7] 0.500000000 0.691462457 0.841344714 0.933192790 0.977249861 0.993790329
#> [13] 0.998650074

p <- as_mlx(c(0.025, 0.5, 0.975))
mlx_qnorm(p)
#> mlx array [3]
#>   dtype: float32
#>   device: gpu
#>   values:
#> [1] -1.959964  0.000000  1.959964