are.pargld.valid | R Documentation |
Is the distribution parameter object consistent with the corresponding distribution? The distribution functions (cdfgld
, pdfgld
, quagld
, and lmomgld
) require consistent parameters to return the cumulative probability (nonexceedance), density, quantile, and L-moments of the distribution, respectively. These functions internally use the are.pargld.valid
function.
are.pargld.valid(para, verbose=FALSE, nowarn=FALSE)
para |
A distribution parameter list returned by |
verbose |
A logical switch on additional output to the user—default is |
nowarn |
A logical switch on warning suppression. If |
Karian and Dudewicz (2000) outline valid parameter space of the Generalized Lambda distribution. First, according to Theorem 1.3.3 the distribution is valid if and only if
\alpha(\kappa F^{\kappa - 1} + h(1-F)^{h -1 }) \ge 0 \mbox{.}
for all F \in [0,1]
. The are.pargld.valid
function tests against this condition by incrementing through [0,1]
by dF = 0.0001
. This is a brute force method of course. Further, Karian and Dudewicz (2002) provide a diagrammatic representation of regions in \kappa
and h
space for suitable \alpha
in which the distribution is valid. The are.pargld.valid
function subsequently checks against the 6 valid regions as a secondary check on Theorem 1.3.3. The regions of the distribution are defined for suitably choosen \alpha
by
\mbox{Region 1: } \kappa \le -1 \mbox{ and } h \ge 1 \mbox{,}
\mbox{Region 2: } \kappa \ge 1 \mbox{ and } h \le -1 \mbox{,}
\mbox{Region 3: } \kappa \ge 0 \mbox{ and } h \ge 0 \mbox{,}
\mbox{Region 4: } \kappa \le 0 \mbox{ and } h \le 0 \mbox{,}
\mbox{Region 5: } h \ge (-1/\kappa) \mbox{ and } -1 \ge \kappa \le 0 \mbox{, and}
\mbox{Region 6: } h \le (-1/\kappa) \mbox{ and } h \ge -1 \mbox{ and } \kappa \ge 1 \mbox{.}
TRUE |
If the parameters are |
FALSE |
If the parameters are not |
This function calls is.gld
to verify consistency between the distribution parameter object and the intent of the user.
W.H. Asquith
Asquith, W.H., 2007, L-moments and TL-moments of the generalized lambda distribution: Computational Statistics and Data Analysis, v. 51, no. 9, pp. 4484–4496.
Karian, Z.A., and Dudewicz, E.J., 2000, Fitting statistical distributions—The generalized lambda distribution and generalized bootstrap methods: CRC Press, Boca Raton, FL, 438 p.
is.gld
, pargld
## Not run:
para <- vec2par(c(123,34,4,3),type='gld')
if(are.pargld.valid(para)) Q <- quagld(0.5,para)
# The following is an example of inconsistent L-moments for fitting but
# prior to lmomco version 2.1.2 and untrapped error was occurring.
lmr <- lmoms(c(33, 37, 41, 54, 78, 91, 100, 120, 124))
para <- pargld(lmr); are.pargld.valid(para)
## End(Not run)
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