topic_statistics(1)

✨ Topic: statistics ✨

okay bestie, welcome to topic_statistics(1) from the GRASS GIS User's Manual 💖 this is the whole squad of GRASS modules that do stats things — univariate, multivariate, kappa, quantiles, the works. no cap, it's a lot, but we're going through every single one. grab a snack 🍓

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🌸 The lineup 🌸

• d.correlate — draws you a lil graph of how two raster maps correlate, and yes it does them in pairs 🦋
• db.univar — does univariate stats on a column you pick from a table 💅
• i.cca — Canonical components analysis (CCA), for image processing ✨
• r.clump — recategorizes a raster map by smooshing cells that form physically discrete areas into unique categories 🎀
• r.coin — tabulates the mutual occurrence (coincidence) of categories across two raster map layers 👑
• r.covar — spits out a covariance/correlation matrix for the raster map layer(s) you specify 🌈
• r.cross — makes a cross product of the category values from multiple raster map layers ⭐
• r.kappa — calculates the error matrix and the kappa parameter, for accuracy assessment of a classification result 🔥
• r.mode — finds the mode of values in a cover map, but only inside areas that share the same category value in a base map you specify 💜
• r.object.geometry — calculates geometry parameters for raster objects 🧚
• r.quant — produces the quantization file for a floating-point map 🌸
• r.reclass.area — reclasses a raster map that's greater or less than an area size you specify (in hectares) 🦋
• r.regression.line — linear regression from two raster maps: y = a + b*x 📈
• r.regression.multi — multiple linear regression from raster maps ✨
• r.report — reports statistics for raster maps 💖
• r.statistics — calculates category or object oriented statistics 💅
• r.stats — generates area statistics for a raster map 🎀
• r.stats.quantile — computes category quantiles, and it does it with two passes 👀
• r.stats.zonal — category or object oriented statistics, the accumulator-based kind 🌈
• r.support.stats — updates raster map statistics ⭐
• r.univar — univariate statistics from the non-null cells of a raster map 👑
• r3.stats — generates volume statistics for 3D raster maps 🔥
• r3.univar — univariate statistics from the non-null cells of a 3D raster map 💜
• t.rast.univar — univariate statistics from the non-null cells, for each registered raster map of a space time raster dataset 🧚
• t.rast3d.univar — univariate statistics from the non-null cells, for each registered 3D raster map of a space time 3D raster dataset 🌸
• t.vect.univar — univariate statistics of attributes, for each registered vector map of a space time vector dataset 🦋
• v.db.univar — univariate statistics on a selected table column, for a GRASS vector map 💖
• v.kcv — randomly partitions points into test/train sets ✨
• v.normal — tests for normality on vector points 💅
• v.outlier — removes outliers from vector point data 🎀
• v.qcount — indices for quadrat counts of vector point lists 🌈
• v.rast.stats — univariate statistics from a raster map, based on a vector map, then uploads the stats into new attribute columns ⭐
• v.univar — univariate statistics of vector map features 👑

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also, bestie: see the corresponding keyword statistics for additional references — there's more where this came from 🫶

and if you're feeling lost, the indexes got you:

• Main index
• Topics index
• Keywords index
• Graphical index
• Full index

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okay that's the whole page, periodt 💅 this was GRASS 8.4.2 — shoutout to the GRASS Development Team, © 2003-2025, and the whole thing is from the GRASS GIS 8.4.2 Reference Manual. go run some stats, you're the main character of this analysis fr fr 🌟