factor_estimate_normal: factor_estimate_normal
In daviddoret/GRCRToolkit: GRC Toolkit

Description Usage Format Value Fields Inherits Methods Examples

A class for factor estimates based on the normal distribution ("Gaussian").
It may be inherited by subclasses, e.g. to implement complementary estimation techniques.

1	factor_estimate_normal

An object of class R6ClassGenerator of length 24.

An instance of the factor_estimate_normal R6Class.

sd: (numeric, scalar) The standard deviation parameter of the normal distribution.
mean: (numeric, scalar) The mean parameter of the normal distribution.
limit_min_value: A strict lower bound applied to the factor simulation values. If NULL or NA, no lower bound will be applied.
limit_max_value: A strict upper bound applied to the factor simulation values. If NULL or NA, no upper bound will be applied.
limit_min_behavior: One of the following options determining how values will be maintained within limit_min_value: "Limit" (default), "Replace", "Discard". "Limit": When an out of bound value is drawn, apply min/max functions to force it within bounds. "Replace": When an out of bound value is drawn, we replace it until it is within bound. "Discard": When an out of bound value is drawn, remove it from the sample.
limit_max_behavior: One of the following options determining how values will be maintained within limit_max_value: "Limit" (default), "Replace", "Discard". "Limit": When an out of bound value is drawn, apply min/max functions to force it within bounds. "Replace": When an out of bound value is drawn, we replace it until it is within bound. "Discard": When an out of bound value is drawn, remove it from the sample.

factor_estimate

get_random(n = 1, output_class = "vector"): Returns a random sample of size n. Returns a vector by default. If output_class = "data.frame", returns a data.frame with a column "factor_value". This second parameterization may be enriched by R6 subclasses to provide additional columns with complementary information.