Sampler1DNormal: Sampler1DNormal Class

In mlr-org/phng: Define and Work with Parameter Spaces for Complex Algorithms

Sampler1DNormal Class

Description

Normal sampling (potentially truncated) for p_dbl().

Super classes

paradox::Sampler -> paradox::Sampler1D -> paradox::Sampler1DRfun -> Sampler1DNormal

Active bindings

mean

(numeric(1))
Mean parameter of the normal distribution.

sd

(numeric(1))
SD parameter of the normal distribution.

Methods

Public methods

• Sampler1DNormal$new()

• Sampler1DNormal$clone()

Inherited methods

• paradox::Sampler$format()
• paradox::Sampler$print()
• paradox::Sampler$sample()

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Method new()

Creates a new instance of this R6 class.

Usage

Sampler1DNormal$new(param, mean = NULL, sd = NULL)

Arguments

param

(ParamSet)
Domain / support of the distribution we want to sample from. Must be one-dimensional.

mean

(numeric(1))
Mean parameter of the normal distribution. Default is ⁠mean(c(param$lower, param$upper)⁠.

sd

(numeric(1))
SD parameter of the normal distribution. Default is (param$upper - param$lower)/4.

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Method clone()

The objects of this class are cloneable with this method.

Usage

Sampler1DNormal$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

See Also

Other Sampler: Sampler1DCateg, Sampler1DRfun, Sampler1DUnif, Sampler1D, SamplerHierarchical, SamplerJointIndep, SamplerUnif, Sampler

mlr-org/phng documentation built on April 22, 2024, 4:34 p.m.