r.regression.line(1grass)

NAME
r.regression.line - Calculates linear regression from two raster maps: y = a + b*x.

KEYWORDS
raster, statistics, regression

SYNOPSIS
r.regression.line
r.regression.line --help
r.regression.line [-g] mapx=name mapy=name [output=name] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

  Flags:

-g
    Print in shell script style

--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:

mapx=name [required]
    Map for x coefficient

mapy=name [required]
    Map for y coefficient

output=name
    ASCII file for storing regression coefficients (output to screen if file not specified).

DESCRIPTION
r.regression.line calculates a linear regression from two raster maps, according to the formula

y = a + b*x

where

x
y

represent the input raster maps.

Optionally, it saves regression coefficients as a ASCII file. The result includes the following coefficients: offset/intercept (a) and gain/slope (b), correlation coefficient (R), number of elements (N), means (medX, medY), standard deviations (sdX, sdY), and the F test for testing the significance of the regression model as a whole (F).

NOTES
The results for offset/intercept (a) and gain/slope (b) are identical to that obtained from R-stats’s lm() function.

EXAMPLE
Comparison of two DEMs (SRTM and NED, both at 30m resolution), provided in the North Carolina sample dataset:

g.region raster=elev_srtm_30m -p
r.regression.line mapx=elev_ned_30m mapy=elev_srtm_30m
 y = a + b*x
   a (Offset): -1.659279
   b (Gain): 1.043968
   R (sumXY - sumX*sumY/N): 0.894038
   N (Number of elements): 225000
   F (F-test significance): 896093.366283
   meanX (Mean of map1): 110.307571
   sdX (Standard deviation of map1): 20.311998
   meanY (Mean of map2): 113.498292
   sdY (Standard deviation of map2): 23.718307

Using the script style flag AND eval to make results available in the shell:

g.region raster=elev_srtm_30m -p
eval `r.regression.line -g mapx=elev_ned_30m mapy=elev_srtm_30m`
# print result stored in respective variables
echo $a
-1.659279
echo $b
1.043968
echo $R
0.894038

SEE ALSO
d.correlate, r.regression.multi, r.stats

AUTHORS
Dr. Agustin Lobo - alobo at ija.csic.es
Updated to GRASS 5.7 Michael Barton, Arizona State University
Script style output Markus Neteler
Conversion to C module Markus Metz

SOURCE CODE

Available at: r.regression.line source code (history)

Accessed: Friday Apr 04 01:19:28 2025

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