pdflmrq | R Documentation |
This function computes the probability density function of the Linear Mean Residual Quantile Function distribution given parameters computed by parlmrq
. The probability density function is
f(x) = \frac{1 - F(x)}{2\alpha\,F(x) + (\mu - \alpha)}\mbox{,}
where f(x)
is the nonexceedance probability for quantile x
, F(x)
is the cumulative distribution function or nonexceedance probability at x
, \mu
is a location parameter, and \alpha
is a scale parameter.
pdflmrq(x, para)
x |
A real value vector. |
para |
The parameters from |
Probability density (f
) for x
.
W.H. Asquith
Midhu, N.N., Sankaran, P.G., and Nair, N.U., 2013, A class of distributions with linear mean residual quantile function and it's generalizations: Statistical Methodology, v. 15, pp. 1–24.
cdflmrq
, qualmrq
, lmomlmrq
, parlmrq
lmr <- lmoms(c(3, 0.05, 1.6, 1.37, 0.57, 0.36, 2.2))
pdflmrq(3,parlmrq(lmr))
## Not run:
para.lmrq <- list(para=c(2.1043, 0.4679), type="lmrq")
para.wei <- vec2par(c(0,2,0.9), type="wei") # note switch from Midhu et al. ordering.
F <- seq(0.01,0.99,by=.01); x <- qualmrq(F, para.lmrq)
plot(x, pdflmrq(x, para.lmrq), type="l", ylab="", lwd=2, lty=2, col=2,
xlab="The p.d.f. of Weibull and p.d.f. of LMRQD", xaxs="i", yaxs="i",
xlim=c(0,9), ylim=c(0,0.8))
lines(x, pdfwei(x, para.wei))
mtext("Midhu et al. (2013, Statis. Meth.)")
## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.