Logistic distribution functions — mlx

Compute density (mlx_dlogis), cumulative distribution (mlx_plogis), and quantile (mlx_qlogis) functions for the logistic distribution using MLX.

Usage

mlx_dlogis(
  x,
  location = 0,
  scale = 1,
  log = FALSE,
  device = mlx_default_device()
)

mlx_plogis(x, location = 0, scale = 1, device = mlx_default_device())

mlx_qlogis(p, location = 0, scale = 1, device = mlx_default_device())

Arguments

x: Vector of quantiles (mlx array or coercible to mlx)
location, scale: Location and scale parameters (default: 0, 1)
log: If TRUE, return log density for mlx_dlogis (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.

Examples

x <- as_mlx(seq(-3, 3, by = 0.5))
mlx_dlogis(x)
#> mlx array [13]
#>   dtype: float32
#>   device: cpu
#>   values:
#>  [1] 0.04517667 0.07010371 0.10499357 0.14914644 0.19661194 0.23500369
#>  [7] 0.25000000 0.23500372 0.19661194 0.14914645 0.10499360 0.07010371
#> [13] 0.04517666
mlx_plogis(x)
#> mlx array [13]
#>   dtype: float32
#>   device: cpu
#>   values:
#>  [1] 0.04742588 0.07585818 0.11920293 0.18242553 0.26894143 0.37754068
#>  [7] 0.50000000 0.62245935 0.73105860 0.81757444 0.88079703 0.92414182
#> [13] 0.95257413

p <- as_mlx(c(0.25, 0.5, 0.75))
mlx_qlogis(p)
#> mlx array [3]
#>   dtype: float32
#>   device: cpu
#>   values:
#> [1] -1.098612  0.000000  1.098612