| pdfpdq4 | R Documentation |
This function computes the probability density of the Polynomial Density-Quantile4 distribution given parameters (\alpha and \beta) computed by parpdq4. The probability density function has not explicit form. The implementation here simply uses a five-point stencil to approciate the derivative of the cumulative distribution function cdfpdq4 and hence an eps term is used and multipled to the scale parameter (\alpha) of the distribution. The distribution's canonical definition is in terms of the quantile function (quapdq4).
pdfpdq4(x, para, paracheck=TRUE, h=NA, hfactor=0.2)
x |
A real value vector. |
para |
The parameters from |
paracheck |
A logical switch as to whether the validity of the parameters should be checked. Default is |
h |
The differential element of the stencil, if provided, otherwise |
hfactor |
A term multiplied to the |
Probability density (f) for x.
W.H. Asquith
Hosking, J.R.M., 2007, Distributions with maximum entropy subject to constraints on their L-moments or expected order statistics: Journal of Statistical Planning and Inference, v. 137, no. 9, pp. 2870–2891, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jspi.2006.10.010")}.
cdfpdq4, quapdq4, lmompdq4, parpdq4, pdfpdq3
## Not run:
para <- list(para=c(0, 0.4332, -0.7029), type="pdq4")
X <- seq(-4, +4, by=(4 - -4) / 1000)
plot( X, pdfpdq4(X, para), type="l", col=grey(0.8), lwd=4, ylim=c(0, 0.5))
lines(X, dnorm( X, sd=1), lty=2)
legend("topleft", c("Standard normal distribution",
"PDQ4 distribution with same L-moments as the standard normal"),
lwd=c(1, 4), lty=c(2, 1), col=c(1, grey(0.8)), cex=0.8)
mtext("Mimic Hosking (2007, fig. 3 [left])")
check.pdf(pdfpdq4, para, hfactor=0.3)
## End(Not run)
## Not run:
para <- list(para=c(100, 43.32, -0.7029), type="pdq4")
minX <- quapdq4(0.0001, para)
maxX <- quapdq4(0.9999, para)
X <- seq(minX, maxX, by=(maxX - minX) / 1000)
plot( X, pdfpdq4(X, para), type="l", col=grey(0.8), lwd=4)
check.pdf(pdfpdq4, para, hfactor=0.3)
## End(Not run)
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