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Kernel smoothing by M.C. Jones, M.P. Wand

Kernel smoothing M.C. Jones, M.P. Wand ebook
Page: 222
Format: djvu
Publisher: Chapman & Hall
ISBN: 0412552701, 9780412552700

Not enough to the smaller ones. Kernel smoothing density estimate for circular data (Scripts) 1.0, Downloads: 98, License: Shareware, By: Vlad Atanasiu, Size: 0.01. The estimated function is smooth, and the level of smoothness is set by a single parameter. A "smoothing kernel," an equation for evaluating noisy data, is often used in the process, but there's an art to choosing the right equation, and a different kernel can give very different results. (and can over-smoothing be tuned/quantified?) I don't know if smoothing along one direction independently of the other makes sense, or if it's better to smooth in 2D. The technique involves using what is called “kernel smoothing”. Instead of using those methods and just choosing a bin size, I decided to smooth things out, and create an average histogram. This is a companion to Matlab's Statistics toolbox ksdensity function and Philipp Berens' CircStat toolbox. Little or no training is required for operation of the kernel smoother. Greetings, The image on the left appears to have been created with Point Density, and the image on the right with Kernel Density. The above methods apply in two dimensions (left-right).