![]() If you know for sure your data con will end up being well-déscribed by a Gáussian, and can be fairly well-distributed over your whole a -range, you can linearize the problem (these are usually equations, not really statements). Youll discover ready-made implementations right here, or here, or here for 2D, or right here (if you have got the statistics toolbox) (have got you heard of Google:). If I have got a group of data factors around back button-100, with con -values corresponding to the regular normal presently there, and a lot of similar ideals around times-2, the entail of all those points will certainly not be zero, and the regular change will certainly not become unity. Possess you attempted that Otherwise, if you possess the stats tool kit, make use of normfit(). The FWHM part I can perform, I already possess a program code for that but Im getting trouble writing program code to suit the Gaussian. Gaussian Elimination Octave Code For That Gaussian Elimination Octave By toponipo1975 Follow | Public
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |