[R] Overdetermined systems

Hello, I have a simple overdetermined system coming from physical measurements. I would like to know if there is a simple way to compute the result of such a system in R. I am aware of the package chebR and the least square methods to provide an optimal solution. But I am really interested in th

[R] Fitting with error on data

As this forum proved to be very helpful, I got another question... I'd like to fit data points on which I have an error, dx and dy, on each x and y. What would be the common procedure to fit this data by a linear model taking into account uncertainty on each point? Would weighting each point by 1/

Re: [R] Uncertainty propagation

Thanks for the help, I start to get reasonable errors on the model... I finally turned to the simpler lm() fitting. As my data from which I fit has only 8 points in each case, I guess it does not make much sense to downweight outliers and use rlm() in this case. -- View this message in contex

Re: [R] Uncertainty propagation

Thanks a lot for the help, I linearized my power relations en fitted them with a linear rlm() function. When I re-sample my pairs from a bivariate normal distribution for my power law what transformation do I need to apply a transformation to my covariance (vcov) matrix to get back from my linear

[R] Uncertainty propagation

I have a small model running under R. This is basically running various power-law relations on a variable (in this case water level in a river) changing spatially and through time. I'd like to include some kind of error propagation to this. My first intention was to use a kind of monte carlo routi

[R] GRASS raster data processing

Hi, I just imported two raster maps into R using the SPGRASS6 package, one containing elevation data and the other containing an erosion index: Kar_inc <-readRAST6("Incis_Kar", plugin=FALSE) Kar_dem <- readRAST6("DEM_Kar", plugin=FALSE) I just wanted to make a xy plot of erosion parameter vs el