LogNormalDistribution: Get a log normal distribution wrapper

In terminological/classifier-result:

Description

Get a log normal distribution wrapper

Get a log normal distribution wrapper

Super class

ClassifierResult::Distribution -> LogNormalDistribution

Public fields

mu

the mean of the normal distribuition

sigma

the sd of the normal distribuition

Methods

Public methods

• LogNormalDistribution$new()

• LogNormalDistribution$label()

• LogNormalDistribution$theoreticalEntropy()

• LogNormalDistribution$clone()

Inherited methods

• ClassifierResult::Distribution$bigP()

• ClassifierResult::Distribution$getInverseCdf()

• ClassifierResult::Distribution$getPdf()

• ClassifierResult::Distribution$inverse()

• ClassifierResult::Distribution$p()

• ClassifierResult::Distribution$plot()

• ClassifierResult::Distribution$q()

• ClassifierResult::Distribution$sample()

• ClassifierResult::Distribution$twoDp()

---

Method new()

get a LogNormal distribution based on tow paramteretisation options - mean and sd (on natural scale) or mode and sd (on natural scale)

Usage

LogNormalDistribution$new(
  mode = runif(1, 1, 4),
  sd = runif(1, 0.5, 5),
  mean = NA
)

Arguments

mode

the mode on a natural scale

sd

the standard deviation on a natural scale

mean

the mean on a natural scale

---

Method label()

gets a label for this distribution based on the parameters passed

Usage

LogNormalDistribution$label()

Returns

a string

---

Method theoreticalEntropy()

calculates the theoretical differential entropy

Usage

LogNormalDistribution$theoreticalEntropy()

Returns

a value

---

Method clone()

The objects of this class are cloneable with this method.

Usage

LogNormalDistribution$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

terminological/classifier-result documentation built on March 14, 2020, 8:04 a.m.