Lnorm-class {distr}R Documentation

Class "Lnorm"

Description

The log normal distribution has density

d(x) = 1/(sqrt(2 pi) sigma x) e^-((log x - mu)^2 / (2 sigma^2))

where μ, by default =0, and σ, by default =1, are the mean and standard deviation of the logarithm. C.f. rlnorm

Objects from the Class

Objects can be created by calls of the form Lnorm(meanlog, sdlog). This object is a log normal distribution.

Slots

img:
Object of class "Reals": The space of the image of this distribution has got dimension 1 and the name "Real Space".
param:
Object of class "LnormParameter": the parameter of this distribution (meanlog and sdlog), declared at its instantiation
r:
Object of class "function": generates random numbers (calls function rlnorm)
d:
Object of class "function": density function (calls function dlnorm)
p:
Object of class "function": cumulative function (calls function plnorm)
q:
Object of class "function": inverse of the cumulative function (calls function qlnorm)

Extends

Class "AbscontDistribution", directly.
Class "UnivariateDistribution", by class "AbscontDistribution".
Class "Distribution", by class "AbscontDistribution".

Methods

initialize
signature(.Object = "Lnorm"): initialize method
meanlog
signature(object = "Lnorm"): returns the slot meanlog of the parameter of the distribution
meanlog<-
signature(object = "Lnorm"): modifies the slot meanlog of the parameter of the distribution
sdlog
signature(object = "Lnorm"): returns the slot sdlog of the parameter of the distribution
sdlog<-
signature(object = "Lnorm"): modifies the slot sdlog of the parameter of the distribution
*
signature(e1 = "Lnorm", e2 = "numeric"): For the Lognormal distribution we use its closedness under positive scaling transformations.

Note

The mean is E(X) = exp(μ + 1/2 σ^2), and the variance Var(X) = exp(2*mu + sigma^2)*(exp(sigma^2) - 1) and hence the coefficient of variation is sqrt(exp(sigma^2) - 1) which is approximately σ when that is small (e.g., σ < 1/2).

Author(s)

Thomas Stabla statho3@web.de,
Florian Camphausen fcampi@gmx.de,
Peter Ruckdeschel Peter.Ruckdeschel@itwm.fraunhofer.de,
Matthias Kohl Matthias.Kohl@stamats.de

See Also

LnormParameter-class AbscontDistribution-class Reals-class rlnorm

Examples

L <- Lnorm(meanlog=1,sdlog=1) # L is a lnorm distribution with mean=1 and sd=1.
r(L)(1) # one random number generated from this distribution, e.g. 3.608011
d(L)(1) # Density of this distribution is 0.2419707 for x=1.
p(L)(1) # Probability that x<1 is 0.1586553.
q(L)(.1) # Probability that x<0.754612 is 0.1.
meanlog(L) # meanlog of this distribution is 1.
meanlog(L) <- 2 # meanlog of this distribution is now 2.

[Package distr version 2.0.6 Index]