cdf2quantile | R Documentation |
Numerically calculate a quantile from a distribution function.
cdf2quantile(p, cdf, interval = c(-3, 3), lower = min(interval), upper = max(interval), ...)
p |
a number in the interval (0,1). |
cdf |
cumulative distribution function, a function. |
interval |
interval in which to look for the root, see Details. |
lower |
lower end point of the interval. |
upper |
upper end point of the interval. |
... |
any further arguments to be passed to the root finding function and the cdf, see Details. |
The quantile, q, is computed numerically as the solution of the equation cdf(q)-p=0.
Function uniroot
is used to find the root. To request higher
precision, set argument tol
. Other arguments in ...
are
passed on to cdf
.
uniroot
needs an interval where to look for the root.
There is a default one, which is extended automatically if it does not
contain the quantile. This assumes that argument cdf
is an
increasing function (as it should be).
To override the default interval, use argument interval
(a
vector of two numbers) or lower
and/or upper
. This may
be necessary if the support of the distribution is not the whole real
line and cdf
does not cope with values outside the support of
the distribution.
The computed quantile as a number.
Georgi N. Boshnakov
plotpdf
cdf2quantile(0.95, pnorm) cdf2quantile(0.05, pexp) # support [0,Inf) is no problem for cdf2quantile(0.05, plnorm) # for built-in distributions. ## default predicision is about 4 digits after decimal point cdf2quantile(0.95, pnorm, mean = 3, sd = 1) cdf2quantile(0.05, pnorm, mean = 3, sd = 1) qnorm(c(0.95, 0.05), mean = 3, sd = 1) ## request a higher precision: cdf2quantile(0.05, pnorm, mean = 3, sd = 1, tol = 1e-8) cdf2quantile(0.05, pnorm, mean = 3, sd = 1, tol = 1e-12) ## see also examples for plotpdf()
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