Estimate quantiles of distribution
estQdf(p, x, cdf)
A vector of probabilities.
The x-axis values corresponding to the cumulative distribution function.
A cumulative distributions function, i.e. output of
Quantiles are obtained in the following manner. For p = 0 and p = 1,
the minimum and maximum of x is used. For other probabilities the quantiles are obtained
q[i] = uniroot(x, cdf - p[i])$root. Y values are interpolated via
Quantiles of cumulative distribution function(s). If the input was a matrix of cumulative distributions functions, a matrix of quantiles is returned.
1 2 3 4 5 6 7 8
x = seq(-9, 9, .1) # x-grid d = dnorm(x) # density functions p = seq(0, 1, .2) # probabilities of interest cEst = estCdf(d) # estimate cumulative distribution functions qEst = estQdf(p = p, x = x, cdf = cEst) # estimate quantiles plot(x, cEst, bty = 'n', las = 1, type = 'l', ylab = 'Probability') # plot cdf abline(h = p, v = qEst, col = 1:6, lty = 2) # add lines for p and for obtained quantiles points(x = qEst, y = p, pch = 18, col = 1:6, cex = 1.75) # add points for intersections
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.