freq.curve.CCC
functions that compute frequency curves for the L-moments. Frequency curves in hydrologic science is a term typically renaming the more conventional quantile function. The notation
CCC
represents the three character notation for the distribution:
exp
, gam
, gev
, gld
, glo
, gno
, gpa
,
gum
, kap
, nor
, pe3
, and wak
. The Cauchy distribution
is not called because of its dependency on trimmed L-moments and its general lack of use in applied
research problems (at least those familiar to the author).freq.curve.all(lmom,aslog10=FALSE,asprob=TRUE,
no2para=FALSE,no3para=FALSE,
no4para=FALSE,no5para=FALSE,
step=FALSE,show=FALSE,
xmin=NULL,xmax=NULL,xlim=NULL,
ymin=NULL,ymax=NULL,ylim=NULL,
exp=TRUE,gam=TRUE,gev=TRUE,gld=FALSE,
glo=TRUE,gno=TRUE,gpa=TRUE,gum=TRUE,
kap=TRUE,nor=TRUE,pe3=TRUE,wak=TRUE,...)
lmom.ub
or similar.log10
of quantiles--note that NaNs produced in: log(x, base) will be produced for less than zero values.qnorm
function is used to convert nonexceedance probabilities, which are produced by nonexceeds
, to standard normal deviations. The normal distribution will plot as straight line when thTRUE
, do not run the 2-parameter distributions: exp
, gam
, gum
, and nor
.TRUE
, do not run the 3-parameter distributions: gev
, glo
, gno
, gpa
, and pe3
.TRUE
, do not run the 4-parameter distributions: kap
and gld
.TRUE
, do not run the 5-parameter distributions: wak
.plot
.show=TRUE
.show=TRUE
.show=TRUE
.show=TRUE
.show=TRUE
.show=TRUE
.TRUE
.TRUE
.TRUE
.TRUE
.TRUE
.TRUE
.TRUE
.TRUE
.TRUE
.TRUE
.TRUE
.TRUE
.parexp
.data.frame
of frequency curves. The nonexceedance probability values, which are provided by nonexceeds
, are the first item in the data.frame
under the heading of nonexceeds
. If a particular distribution could not be fit to the L-moments of the data; this particular function returns zeros so that a data.frame
can be returned.freq.curve.exp
,
freq.curve.gam
,
freq.curve.gev
,
freq.curve.gld
,
freq.curve.glo
,
freq.curve.gno
,
freq.curve.gpa
,
freq.curve.gum
,
freq.curve.kap
,
freq.curve.nor
,
freq.curve.pe3
, and
freq.curve.wak
L <- vec2lmom(c(35612,23593,0.48,0.21,0.11))
freq.curve.all(L,gld=FALSE)
freq.curve.all(L,step=TRUE,no2para=TRUE,no4para=TRUE)
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