What do quantiles mean here? If you have a mixture density, say
myf <- function(x,p0) p0*dbeta(x,2,6) + (1-p0)*dbeta(x,6,2)
then I know what quantiles mean. To find the Pth quantile use uniroot
to solve for the x such that myf(x,p0) - P =0.
albyn
Quoting VictorDelgado <victor.m...@fjp.mg.gov.br>:
Gerhard wrote
Suppose I create a custom function, consisting of two beta-distributions:
myfunction <- function(x) {
dbeta(x,2,6) + dbeta(x,6,2)
}
How can I calculate the quantiles of myfunction?
Thank you in advance,
Gerhard
Gehard, if do you want to know the quantiles of the new distribution created
by "myfunction". Maybe you can also do:
x <- seq(0,1,.01) # insert your 'x'
q <- myfunction(x)
# And:
quantile(x)
0% 25% 50% 75% 100%
0.000000 1.476177 2.045389 2.581226 2.817425
# This gives the sample quantiles. You can also look foward to simulations
(like Bert Gunter had suggested) to know better the properties of
distributions quantiles obtained after 'myfunction'.
-----
Victor Delgado
cedeplar.ufmg.br P.H.D. student
www.fjp.mg.gov.br reseacher
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