2011/9/30 António Rocha <[email protected]>: > I > > I have been using r.series to calculate a linear regression slope for an old > and new raster map using r.series. But now I need to also obtain the error. > It seems not to be possible to use r.series. Is this true? if yes, what > alternative do I have?
In your case, the error is always zero. This is because the regression equation is based on only two maps. Just for clarification, r.series does not calculate a linear regression between raster maps. r.series can calculate a linear regression between raster values and the order number of raster maps, and this is done for each cell separately. For example, with 4 input maps map1,map2,map3,map4, r.series calculates the regression coefficients for each cell for x = (1, 2, 3, 4) and y = (value of map1 and current cell, value of map2 and current cell, value of map3 and current cell, value of map4 and current cell). The general form of a linear regression is y = b0 + b1 * x1 + b2 * x2 + ... + bn * xn + error with n = number of explaining variables With only one explaining variable, this reduces to y = b0 + b1 * x1 + error with b0 = offset, b1 = slope With only two values available for x and y, this reduces to y = b0 + b1 * x1 i.e. no error, the regression line passes exactly through the two given points. In your case, there are only two points per cell, the first point is (1, value of map1 at current cell), the second point is (2, value of map2 at current cell). The regression coefficients of r.series are interesting for time series maps to detect trends in time, e.g. correlating temperature with time (implied by the order of the input maps). r.regression.line calculates regression coefficients between two raster maps which is something completely different. Markus M _______________________________________________ grass-user mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/grass-user
