Actually, there are other useful answers (Ive read another interesting one by Jake, but I cant find it now) on the site: perhaps a deeper search is worth. With two built-in functions - the normal distribution norm() and the inverse normal distribution invnorm() - of Gnuplot one can draw the normal probability axis. These references might help you: How to Draw CDF of normal distribution in Tikz and Draw a bivariate normal distribution in TikZ. Recycling data from the previous example we can plot both data and best fit model (in plot 1) and residuals (in plot 2): "f(x) = a * sin(b :- "a=$(vars.a)" "b=$(vars.b)" :- name=>(x, y, :- "set multiplot layout :- 1 "p $name w errorbars t :- "p $name u 1:(f(\$1)) w l t 'Best fit :- 2 "p $name u 1:((f(\$1)-\$2) / \$3):(1) w errorbars t 'Resid. where the function is evaluated giving the cumulative probability of the normal distribution from minus infinity to the specified point normalx(i,xval) in a. It often shows a 'log normal distribution', which becomes a straight line on the 'normal probability'(fraction) vs log(size) plot, and so called 'normal probability axis' is used. Each plot is identified by a positive integer number, which can be used as argument to to redirect commands to the appropriate plot. Gnuplot.jl can draw multiple plots in the same figure by exploiting the multiplot command. │ ~/.julia/packages/DocumentationGenerator/8gp6G/src/rundocumenter.jl:51 │ ~/.julia/packages/Documenter/e77Rr/src/Documenter.jl:190 │ getproperty(x::NamedTuple, dir::String) C = vars.c) ┌ Error: Exception while generating log record in module Main.ex-abc at none:1
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