NAME

r.quantile - Compute quantiles using two passes.

KEYWORDS

raster, algebra, statistics, percentile, quantile

SYNOPSIS

r.quantile
r.quantile --help
r.quantile [-r] input=name [quantiles=integer] [percentiles=float[,float,...]] [bins=integer] [file=name] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

-r: Generate recode rules based on quantile-defined intervals
--overwrite: Allow output files to overwrite existing files
--help: Print usage summary
--verbose: Verbose module output
--quiet: Quiet module output
--ui: Force launching GUI dialog

Parameters:

input=name [required]: Name of input raster map
quantiles=integer: Number of quantiles
Default: 4
percentiles=float[,float,...]: List of percentiles
bins=integer: Number of bins to use
Default: 1000000
file=name: Name for output file (if omitted or "-" output to stdout)

DESCRIPTION

r.quantile computes quantiles in a manner suitable for use with large amounts of data. It is using two passes.

NOTES

Quantiles are calculated following algorithm 7 from Hyndman and Fan (1996), which is also the default in R and numpy.

EXAMPLE

Calculation of elevation quantiles (printed to standard-out):

g.region raster=elevation -p
r.quantile input=elevation percentiles=0.1,1,10,25,50,75,90,99,99.9

The output of r.quantile can be used for quantile classification:

g.region raster=elevation -p
r.quantile elevation quantiles=5 -r --quiet | r.recode elevation \


           out=elev_quant5 rules=-

REFERENCES

Hyndman and Fan (1996) Sample Quantiles in Statistical Packages, American Statistician. American Statistical Association. 50 (4): 361-365. DOI: 10.2307/2684934
Engineering Statistics Handbook: Percentile, NIST

AUTHORS

Glynn Clements
Markus Metz

SOURCE CODE

Available at: r.quantile source code (history)

Latest change: Thursday Jan 26 14:10:26 2023 in commit: cdd84c130cea04b204479e2efdc75c742efc4843