Speaking Stata: Density probability plots
Abstract. Density probability plots show two guesses at the density function of a
continuous variable, given a data sample. The first guess is the density
function of a specified distribution (e.g., normal, exponential, gamma,
etc.) with appropriate parameter values plugged in. The second guess is the
same density function evaluated at quantiles corresponding to plotting
positions associated with the sample’s order statistics. If the
specified distribution fits well, the two guesses will be close. Such
plots, suggested by Jones and Daly in 1995, are explained and discussed with
examples from simulated and real data. Comparisons are made with histograms,
kernel density estimation, and quantile–quantile plots.
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Nicholas J. Cox
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density probability plots, distributions, histograms, kernel density estimation, quantile–quantile plots, statistical graphics
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