lrzlmomco | R Documentation |
This function computes the Lorenz Curve for quantile function x(F)
(par2qua
, qlmomco
). The function is defined by Nair et al. (2013, p. 174) as
L(u) = \frac{1}{\mu}\int_0^u x(p)\; \mathrm{d}p\mbox{,}
where L(u)
is the Lorenz curve for nonexceedance probability u
. The Lorenz curve is related to the Bonferroni curve (B(u)
, bfrlmomco
) by
L(u) = \mu B(u)\mbox{.}
lrzlmomco(f, para)
f |
Nonexceedance probability ( |
para |
The parameters from |
Lorzen curve value for F
.
W.H. Asquith
Nair, N.U., Sankaran, P.G., and Balakrishnan, N., 2013, Quantile-based reliability analysis: Springer, New York.
qlmomco
, bfrlmomco
# It is easiest to think about residual life as starting at the origin, units in days.
A <- vec2par(c(0.0, 2649, 2.11), type="gov") # so set lower bounds = 0.0
f <- c(0.25, 0.75) # Both computations report: 0.02402977 and 0.51653731
Lu1 <- lrzlmomco(f, A)
Lu2 <- f*bfrlmomco(f, A)
# The Lorenz curve is related to the Gini index (G), which is L-CV:
"afunc" <- function(u) { return(lrzlmomco(f=u, A)) }
L <- integrate(afunc, lower=0, upper=1)$value
G <- 1 - 2*L # 0.4129159
G <- 1 - expect.min.ostat(2,para=A,qua=quagov)*cmlmomco(f=0,A) # 0.4129159
LCV <- lmomgov(A)$ratios[2] # 0.41291585
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