> >> about a year ago I developed for my own purposes a routine for averaging > >> irregularly-sampled data using gaussian average. > > > > is this similar to Kernel Density estimation? > > > > http://www.scipy.org/doc/api_docs/SciPy.stats.kde.gaussian_kde.html > > No. It is probably closer to radial basis function interpolation (in fact, it > almost certainly is a form of RBFs): > > http://docs.scipy.org/doc/scipy/reference/tutorial/interpolate.html#id1
I checked the official terminology, it is a kernel average smoother (in the sense of [1]) with special weight function exp(-(x-x0)^2/const), operating on irregularly-spaced data in 2d. I am not sure if that is the same as what scipy.stats.kde.gaussian_kde does, the documentation is terse. Can I be enlightened here? Cheers, Vaclav [1] http://en.wikipedia.org/wiki/Kernel_smoothing ------------------------------------------------------------------------------ Come build with us! The BlackBerry® Developer Conference in SF, CA is the only developer event you need to attend this year. Jumpstart your developing skills, take BlackBerry mobile applications to market and stay ahead of the curve. Join us from November 9-12, 2009. Register now! http://p.sf.net/sfu/devconf _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
