# lmr-functions: L-moments of specific probability distributions In lmom: L-Moments

 lmr-functions R Documentation

## L-moments of specific probability distributions

### Description

Computes the L-moments of a probability distribution given its parameters. The following distributions are recognized:

 lmrexp exponential lmrgam gamma lmrgev generalized extreme-value lmrglo generalized logistic lmrgpa generalized Pareto lmrgno generalized normal lmrgum Gumbel (extreme-value type I) lmrkap kappa lmrln3 three-parameter lognormal lmrnor normal lmrpe3 Pearson type III lmrwak Wakeby lmrwei Weibull

### Usage

lmrexp(para = c(0, 1), nmom = 2)
lmrgam(para = c(1, 1), nmom = 2)
lmrgev(para = c(0, 1, 0), nmom = 3)
lmrglo(para = c(0, 1, 0), nmom = 3)
lmrgno(para = c(0, 1, 0), nmom = 3)
lmrgpa(para = c(0, 1, 0), nmom = 3)
lmrgum(para = c(0, 1), nmom = 2)
lmrkap(para = c(0, 1, 0, 0), nmom = 4)
lmrln3(para = c(0, 0, 1), nmom = 3)
lmrnor(para = c(0, 1), nmom = 2)
lmrpe3(para = c(0, 1, 0), nmom = 3)
lmrwak(para = c(0, 1, 0, 0, 0), nmom = 5)
lmrwei(para = c(0, 1, 1), nmom = 3)

### Arguments

 para Numeric vector containing the parameters of the distribution. nmom The number of L-moments to be calculated.

### Details

Numerical methods and accuracy are as described in Hosking (1996, pp. 8–9).

### Value

Numeric vector containing the L-moments.

### Author(s)

J. R. M. Hosking jrmhosking@gmail.com

### References

Hosking, J. R. M. (1996). Fortran routines for use with the method of L-moments, Version 3. Research Report RC20525, IBM Research Division, Yorktown Heights, N.Y.

lmrp to compute L-moments of a general distribution specified by its cumulative distribution function or quantile function.

samlmu to compute L-moments of a data sample.

pelexp, etc., to compute the parameters of a distribution given its L-moments.

For individual distributions, see their cumulative distribution functions:

 cdfexp exponential cdfgam gamma cdfgev generalized extreme-value cdfglo generalized logistic cdfgpa generalized Pareto cdfgno generalized normal cdfgum Gumbel (extreme-value type I) cdfkap kappa cdfln3 three-parameter lognormal cdfnor normal cdfpe3 Pearson type III cdfwak Wakeby cdfwei Weibull

### Examples

# Compare sample L-moments of Ozone from the airquality data
# with the L-moments of a GEV distribution fitted to the data
data(airquality)
smom <- samlmu(airquality\$Ozone, nmom=6)
gevpar <- pelgev(smom)
pmom <- lmrgev(gevpar, nmom=6)
print(smom)
print(pmom)

lmom documentation built on Aug. 29, 2023, 9:07 a.m.