lmr-functions {lmom} | R Documentation |
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 (lognormal) |
lmrgum | Gumbel (extreme-value type I) |
lmrkap | kappa |
lmrnor | normal |
lmrpe3 | Pearson type III |
lmrwak | Wakeby |
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) 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)
para |
Numeric vector containing the parameters of the distribution. |
nmom |
The number of L-moments to be calculated. |
Numerical methods and accuracy are as described in Hosking (1996, pp.8-9).
Numeric vector containing the L-moments.
J. R. M. Hosking hosking@watson.ibm.com
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 (lognormal) |
cdfgum | Gumbel (extreme-value type I) |
cdfkap | kappa |
cdfnor | normal |
cdfpe3 | Pearson type III |
cdfwak | Wakeby |
# 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)