lmomsla | R Documentation |
This function estimates the trimmed L-moments of the Slash distribution given the parameters (\xi
and \alpha
) from parsla
. The relation between the TL-moments (trim=1
) and the parameters have been numerically determined and are
\lambda^{(1)}_1 = \xi
,
\lambda^{(1)}_2 = 0.93686275\alpha
,
\tau^{(1)}_3 = 0
,
\tau^{(1)}_4 = 0.30420472
,
\tau^{(1)}_5 = 0
, and
\tau^{(1)}_6 = 0.18900723
.
These TL-moments (trim=1) are symmetrical for the first L-moments defined because \mathrm{E}[X_{1:n}]
and \mathrm{E}[X_{n:n}]
are undefined expectations for the Slash.
lmomsla(para)
para |
The parameters of the distribution. |
An R list
is returned.
lambdas |
Vector of the trimmed L-moments. First element is |
ratios |
Vector of the L-moment ratios. Second element is |
trim |
Level of symmetrical trimming used in the computation, which is |
leftrim |
Level of left-tail trimming used in the computation, which is |
rightrim |
Level of right-tail trimming used in the computation, which is |
source |
An attribute identifying the computational source of the L-moments: “lmomsla” |
trim |
Level of symmetrical trimming used. |
W.H. Asquith
Rogers, W.H., and Tukey, J.W., 1972, Understanding some long-tailed symmetrical distributions: Statistica Neerlandica, v. 26, no. 3, pp. 211–226.
parsla
, cdfsla
, pdfsla
, quasla
## Not run:
# This example was used to numerically back into the TL-moments and the
# relation between \alpha and \lambda_2.
"lmomtrim1" <- function(para) {
bigF <- 0.9999
minX <- para$para[1] - para$para[2]*qnorm(1 - bigF) / qunif(1 - bigF)
maxX <- para$para[1] + para$para[2]*qnorm( bigF) / qunif(1 - bigF)
minF <- cdfsla(minX, para); maxF <- cdfsla(maxX, para)
lmr <- theoTLmoms(para, nmom = 6, leftrim = 1, rightrim = 1)
}
U <- -10; i <- 0
As <- seq(.1,abs(10),by=.2)
L1s <- L2s <- T3s <- T4s <- T5s <- T6s <- vector(mode="numeric", length=length(As))
for(A in As) {
i <- i + 1
lmr <- lmomtrim1(vec2par(c(U, A), type="sla"))
L1s[i] <- lmr$lambdas[1]; L2s[i] <- lmr$lambdas[2]
T3s[i] <- lmr$ratios[3]; T4s[i] <- lmr$ratios[4]
T5s[i] <- lmr$ratios[5]; T6s[i] <- lmr$ratios[6]
}
print(summary(lm(L2s~As-1))$coe)
print(mean(T4s))
print(mean(T6s)) #
## End(Not run)
## Not run:
alpha <- 30
tlmr <- theoTLmoms(vec2par(c(100, alpha), type="cau"), nmom=6, trim=1)
print( c(tlmr$lambdas[2] / alpha, tlmr$ratios[c(4,6)]), 8 ) #
## End(Not run)
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