check_pareto | R Documentation |
The pareto distribution is a power-law probability distribution that describes
the phenomenon that a large portion of xxx (for example, wealth or income) is
concentrated in a small fraction of the population.
check_pareto
takes in a data frame and returns a function for making
ggplot2 type of CDF and CCDF (on a log10-log10 scale) plots side by side on one
canvas of any continuous variable from the data frame. CCDF standands for
Complement CDF. If CCDF on a log10-log10 scale looks like a straight line, the
observed variable is pareto with a shape parameter equal to -slope, and a
location parameter equal to 10^(intercept / -slope).
check_pareto(df)
df |
A data frame. |
function(varname, linew = 0.7, xlab = varname, title_left, title_right,
subtitle_left, subtitle_right, caption_left, caption_right,
digits = 2, ...)
varname. String, name of a continuous variable. Its empirical CDF will be plotted along side its complement CDF.
linew. Number, width of the line. Default = 0.7.
xlab. String, x label of the left and the right figures. Default is varname.
title_left. String, title of the left figure.
title_right. String, title of the right figure.
subtitle_left. String, subtitle of the left figure.
subtitle_right. String, subtitle of the right figure.
caption_left. String, caption of the left figure.
caption_right. String, caption of the right figure.
digits. Integer, the number of digits after the decimal point for the estimated parameter values of the theoretical distribution. Default = 2.
.... Other parameters for making a CDF plot. A common one, for
example, is 'add_vline_median = TRUE', which will add a vertical line at
the median. Another common one is 'show_label_median = FALSE', which
will suppress the display of median value along the median vline. See
mk_cdfplot
for a full list of parameters.
est_params_pareto
for how the parameters of the
theoretical pareto distribution are estimated.
inst/examples/ex-check_pareto.R
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