wtd.pctiles.fast: Show the values at 100 weighted percentiles

In ejanalysis/analyze.stuff: Miscellaneous Tools for Analyzing Data in Rows and Columns

Show the values at 100 weighted percentiles

Description

Get a quick look at a weighted distribution by seeing the 100 values that are the weighted percentiles 1-100

Usage

wtd.pctiles.fast(x, wts = NULL, na.rm = TRUE)

Arguments

x	Required numeric vector of values whose distribution you want to look at.
wts	NULL by default, or vector of numbers to use as weights in Hmisc::wtd.quantile
na.rm	Logical optional TRUE by default, in which case NA values are removed first.

Details

Provides weighted percentiles without using wtd.quantile, see Hmisc::wtd.Ecdf()

Value

Returns a data.frame

NOTE: THIS ONLY SHOWS PERCENTILES AND MEAN FOR THE VALID (NOT NA) VALUES !

Defining these types as type=1 and type="i/n" will create simple discontinuous quantiles, without interpolation where there are jumps in the values analyzed. *** WARNING: Unless set type=1, the default type=7 in which case stats::quantile() FUNCTION INTERPOLATES, WHICH ISN'T OBVIOUS IN EVERY DATASET! use type=1 to avoid interpolation. and pctiles() rounded results so interpolation would be even less apparent.
The quantile function will NOT interpolate between values if type=1:
stats::quantile(1:12, probs=(1:10)/10, type=1)
10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
2 3 4 5 6 8 9 10 11 12
###########################
**** IMPORTANT ***
###########################
*** WARNING: The Hmisc::wtd.quantile function DOES interpolate between values, even if type='i/n'
There does not seem to be a way to fix that for the Hmisc::wtd.quantile() function. For example,
Hmisc::wtd.quantile(1:12, probs=(1:10)/10, type='i/n', weights=rep(1,12))
10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
1.2 2.4 3.6 4.8 6.0 7.2 8.4 9.6 10.8 12.0

See Also

pctiles() pctiles.exact() pctiles.a.over.b() wtd.pctiles.exact() wtd.pctiles() wtd.pctiles.fast()

ejanalysis/analyze.stuff documentation built on April 2, 2024, 10:10 a.m.