rlorenz: Compute relevant probabilities and estimates for selecting...

In glorenz: Transformed and Relative Lorenz Curves for Survey Weighted Data

Compute relevant probabilities and estimates for selecting performance criteria

Description

Compute relevant probabilities and estimates for selecting performance criteria

Usage

rlorenz(p, data, group, edata, newwts = "newwts")

Arguments

p	percentile based on data from group with lower mean value
data	dataset of group with higher mean value.
group	variable of interest. Entered in quotes.Must be present in data and edata.
edata	dataset of group with lower mean value.Must have defined newwts column. Sum of newwts for edata must be equal to sum of newwts for data.
newwts	sampling weights. "newwts" by default. Must be present in data and edata.

Value

Relative Lorenz function value for p

Examples

df_samp <- data.frame(x1 = rnorm(500, mean = 5, sd = 2),newwts = rep(1, 500))
df_samp2 <- data.frame(x1 = rnorm(500, mean = 4.5, sd = 2),newwts = rep(1, 500))
p_vals <- seq(0, 1, length.out = 100)
lc_vals <- rlorenz(p_vals, data = df_samp, group = "x1", edata = df_samp2)

#Creates relative Lorenz curve values for two sets of simulated data

glorenz documentation built on June 8, 2025, 10:46 a.m.