Dear All,
I have a variable q which is a vector of 1000 simulated positive values; that
is I generated 1000 samples from the pareto distribution, from each sample I
calculated the value of q ( a certain fn in the sample observations), and thus
I was left with 1000 values of q and I don't know the distribution of q.
Hence, I used the given code for kernel density estimation to estimate the
density of q
>options(scipen=4)
> d <- density(q, bw = "nrd0",kernel="gaussian")
> d
> plot(d)
But what I'm really intersed in is to estimate the probability that q is
greater than a certain value , for ex.,P(q>11000), using the kernel density
estimate I obtained.
Could u help me with a fn or some document to do this?
Thank u so much
Maram
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