This function takes a parameter object, such as that returned by lmom2par
, and computes the support (the lower and upper bounds, par2qua
for the parameters in argument para
(
lower <- par2qua(0, para) upper <- par2qua(1, para)
The quality of
The intent of this function is to provide a unified portal for
The support returned by this function might be useful in extended application development involving probability density functions pdfCCC
(dlmomco
) and cumulative distribution functions cdfCCC
(plmomco
) functions---both of these functions use as their primary argument a value
supdist(para, trapNaN=FALSE, delexp=0.5, paracheck=TRUE, ...)
The parameters of the distribution.
A logical influencing how NaN
are handled (see Note).
The magnitude of the decrementing of the exponent to search down and up from. A very long-tailed but highly peaked distribution might require this to be smaller than default.
A logical controlling whether the parameters are checked for validity.
Additional arguments to pass.
An R list
is returned.
Three character (minimum) distribution type (for example, type="gev"
);
The support (or range) of the fitted distribution;
The nonexceedance probabilities at the computed support.
A vector indicating how the respective lower and upper boundaries were arrived at (see Note); and
A logical on each entry of the support
with a preemptive call by the is.finite
function in R.
An attribute identifying the computational source of the distribution support: “supdist”.
# NOT RUN {
lmr <- lmoms(c(33, 37, 41, 54, 78, 91, 100, 120, 124))
supdist(lmom2par(lmr, type="gov" )) # Lower = 27.41782, Upper = 133.01470
supdist(lmom2par(lmr, type="gev" )) # Lower = -Inf, Upper = 264.4127
supdist(lmom2par(lmr, type="wak" )) # Lower = 16.43722, Upper = NaN
supdist(lmom2par(lmr, type="wak" ), trapNaN=TRUE) # Lower = 16.43722, Upper = 152.75126
#$support 16.43722 152.75126
#$fexpons NA -16
#$finite TRUE TRUE
# }
# NOT RUN {
para <- vec2par(c(0.69, 0.625), type="kmu") # very flat tails and narrow peak!
supdist(para, delexp=1 )$support # [1] 0 NaN
supdist(para, delexp=0.5 )$support # [1] 0.000000 3.030334
supdist(para, delexp=0.05)$support # [1] 0.000000 3.155655
# This distribution appears to have a limit at PI and the delexp=0.5
# }
Run the code above in your browser using DataLab