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).
r.regression.line calculates a linear regression from two
raster maps, according to the formula
where
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).
The results for offset/intercept (a) and gain/slope (b) are
identical to that obtained from R-stats's lm() function.
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
d.correlate,
r.regression.multi,
r.stats
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)
Main index |
Raster index |
Topics index |
Keywords index |
Graphical index |
Full index
© 2003-2021
GRASS Development Team,
GRASS GIS 7.9.dev Reference Manual