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Editorial Team
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Editorial Team
Asked: May 15, 20262026-05-15T12:32:31+00:00 2026-05-15T12:32:31+00:00

I have a normalization method that uses the normal distribution functions pnorm() and qnorm().

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I have a normalization method that uses the normal distribution functions pnorm() and qnorm(). I want to alter my logic so that I can use empirical distributions instead of assuming normality. I’ve used ecdf() to calculate the empirical cumulative distributions but then realized I was beginning to write a function that basically was the p and q versions of the empirical. Is there a simpler way to do this? Maybe a package with pecdf() and qecdf()? I hate reinventing the wheel.

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  1. Editorial Team
    Editorial Team
    2026-05-15T12:32:32+00:00Added an answer on May 15, 2026 at 12:32 pm

    You can use the quantile and ecdf functions to get qecdf and pecdf, respectively:

    x <- rnorm(20)
    quantile(x, 0.3, type=1) #30th percentile
    Fx <- ecdf(x)
    Fx(0.1)  # cdf at 0.1
    
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