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
## 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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