Class: distribution.continuous.lognormal.class

Derived class for a lognormally-distributed random variable.

Super classes

mastiff::R6.class.class -> mastiff::distribution.abstract.class -> mastiff::distribution.continuous.class -> distribution.continuous.lognormal.class

Active bindings

interfaces

The list of available class interfaces

mean

the mean of the distribution

sd

the standard deviation of the distribution

var

the variance of the distribution

Methods

Public methods

• distribution.continuous.lognormal.class$new()

• distribution.continuous.lognormal.class$d()

• distribution.continuous.lognormal.class$p()

• distribution.continuous.lognormal.class$q()

• distribution.continuous.lognormal.class$r()

• distribution.continuous.lognormal.class$clone()

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Method new()

Create a new object of class distribution.continuous.normal.class

Usage

distribution.continuous.lognormal.class$new(meanlog, sdlog)

Arguments

meanlog

the mean of log(X)

sdlog

the standard deviation of log(X)

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Method d()

Density function for a lognormal random variable with mean log(X) $params$meanlog and standard deviation log(X) $params$sdlog.

Usage

distribution.continuous.lognormal.class$d(x, log = FALSE)

Arguments

x

vector of quantiles.

log

logical; if TRUE, probabilities p are given as log(p).

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Method p()

Cumulative density function for a lognormal random variable with mean log(X) $params$meanlog and standard deviation log(X) $params$sdlog.

Usage

distribution.continuous.lognormal.class$p(q, lower.tail = TRUE, log.p = FALSE)

Arguments

q

vector of quantiles.

lower.tail

logical; if TRUE (default), probabilities are \(P[ X \leq x ]\), otherwise, \(P[X>x]\).

log.p

logical; if TRUE, probabilities p are given as log(p).

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Method q()

Quantile function for a lognormal random variable with mean log(X) $params$meanlog and standard deviation log(X) $params$sdlog.

Usage

distribution.continuous.lognormal.class$q(p, lower.tail = TRUE, log.p = FALSE)

Arguments

p

vector of probabilities.

lower.tail

logical; if TRUE (default), probabilities are \(P[ X \leq x ]\), otherwise, \(P[X>x]\).

log.p

logical; if TRUE, probabilities p are given as log(p).

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Method r()

Generates random deviates for a lognormal random variable with mean log(X) $params$meanlog and standard deviation logx(X) $params$sdlog .

Usage

distribution.continuous.lognormal.class$r(n)

Arguments

n

number of observations. If length( n ) > 1, the length is taken to be the number required.

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Method clone()

The objects of this class are cloneable with this method.

Usage

distribution.continuous.lognormal.class$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.