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HI, I wonder does anyone have experience with doing sequential gaussian simulation with krige() function in gstat? I find it VERY slow compared to use krige() to achieve kriging function itself.. I wonder why, is that because it has to model the variogram, and do the kriging separately for each point to be simulated? so it would be N times slower to achieve the simulation than the kriging if

...It currently installs only on Windows 2000 or XP (NOT on Windows 9X/ME/Millenium, nor any other platform!). You can download it at http://www.sciviews.org. Please, note that the program still does not support path names with spaces, like the default one, "C:\Program Files\SciViews\". You _have to change_ the default value of installation folder in the setup program to something like "c:\Pgm\SciViews\"! Of course, you need also R installed on the same computer (at least version 1.5.0). This package proposes: - Insighter, a GUI specifically designed for data analysis. It offers:...

...for such a backend. Perhaps the reasons for the posting would help? If not, please read no further, just please accept more, sincere thanks and requests for forgiveness. <<DANGER, WILL ROBINSON! LONG EMAIL AHEAD! DANGER!>> My hope was to obtain information about/from projects that _have actually performed_ (or decided _not_ to perform) a task similar to mine. Because... My superordinates have read that it's quick and easy to create an LLVM backend. On 11/27, I was tasked to create a "super basic" LLVM backend for a platform that has no stack--something the core LL...

Thanks, no malloc or free equivalents either (no heap). So, there are no others (to your knowledge) who have built an LLVM backend for a platform with no “normal” stack? I found a presentation about some FPGA work (using LLVM) but it doesn’t seem to apply to my platform. Perhaps someone else on the mailing list will have come across this rarity? Thank you again for your time and

...> do the kriging separately for each point to be simulated? It does not model variograms on the way. It is slower than kriging because it uses the sequential simulation algorithm: for each node visited, a value is simulated, and this value is added to the conditioning data. For this reason you _have to_ limit the search neighbourhood (using the nmax or maxdist arguments) if you're simulating on more than say a few hundred nodes. Taking a very small nmax may yield fast simulations, at the expense of a good representation of the target spatial correlation structure. > > so it would b...