title: Inverse function of an unknown cumulative function
body: <p>I'm working with a data file, the observations inside are random values. In this case I don't know the distribution of x (my observations). I'm using the function density in order to estimate the density, because I must apply a kernel estimation.</p>
  
  <pre><code>T=density(datafile[,1],bw=sj,kernel="epanechnikov")
  </code></pre>
  
  <p>After this I must integrate this because I'm looking for a quantile (similar to VaR, 95%).
  For this I have 2 options:</p>
  
  <pre><code>ecdf()
  quantile()
  </code></pre>
  
  <p>Now I have the value of the quantile 95, but this is the data estimated by kernel.</p>
  
  <p><strong>Is there a function which I can use to know the value of the quantile 95 of the original data?</strong></p>
  
  <p>I remark that this is a distribution unknown, for this I would like to imagine a non parametric method as Newton, like the one that is in SAS <code>solve()</code></p>