Max-entropy and latin hypercube grids — grid_max

These functions are deprecated because they have been replaced by grid_space_filling().

Usage

grid_max_entropy(
  x,
  ...,
  size = 3,
  original = TRUE,
  variogram_range = 0.5,
  iter = 1000
)

# S3 method for class 'parameters'
grid_max_entropy(
  x,
  ...,
  size = 3,
  original = TRUE,
  variogram_range = 0.5,
  iter = 1000
)

# S3 method for class 'list'
grid_max_entropy(
  x,
  ...,
  size = 3,
  original = TRUE,
  variogram_range = 0.5,
  iter = 1000
)

# S3 method for class 'param'
grid_max_entropy(
  x,
  ...,
  size = 3,
  original = TRUE,
  variogram_range = 0.5,
  iter = 1000
)

grid_latin_hypercube(x, ..., size = 3, original = TRUE)

# S3 method for class 'parameters'
grid_latin_hypercube(x, ..., size = 3, original = TRUE)

# S3 method for class 'list'
grid_latin_hypercube(x, ..., size = 3, original = TRUE)

# S3 method for class 'param'
grid_latin_hypercube(x, ..., size = 3, original = TRUE)

Arguments

x: A param object, list, or parameters.
...: One or more param objects (such as mtry() or penalty()). None of the objects can have unknown() values in the parameter ranges or values.
size: A single integer for the maximum number of parameter value combinations returned. If duplicate combinations are generated from this size, the smaller, unique set is returned.
original: A logical: should the parameters be in the original units or in the transformed space (if any)?
variogram_range: A numeric value greater than zero. Larger values reduce the likelihood of empty regions in the parameter space. Only used for type = "max_entropy".
iter: An integer for the maximum number of iterations used to find a good design. Only used for type = "max_entropy".

Examples

grid_latin_hypercube(penalty(), mixture(), original = TRUE)
#> Warning: `grid_latin_hypercube()` was deprecated in dials 1.3.0.
#> ℹ Please use `grid_space_filling()` instead.
#> # A tibble: 3 × 2
#>        penalty mixture
#>          <dbl>   <dbl>
#> 1 0.000378      0.435 
#> 2 0.0000000140  0.0806
#> 3 0.00102       0.974