Kernel smoothing M.C. Jones, M.P. Wand
Publisher: Chapman & Hall
In general cases, when the smoothing factor tends to infinity, minimizing the smoothed error entropy will be approximately equivalent to minimizing error variance, regardless of the conditional PDF and the kernel. The typical kernel is a uniform or a Gaussian kernel. In one kind of image filter, you have an array of values called the filter's kernel. Typically smoothing is a process of convolving a kernel with the image at each pixel location. Kernel Smoothing Exam 4/C - Construction and Evaluation of Actuarial Models. Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. March 3rd, 2013 reviewer Leave a comment Go to comments. For efficiency, SMOOTH divides the kernel width into a running total of the differences between neighboring values. For each pixel in the image, you center the array over that pixel. Wand Publisher: Chapman & Hall. Voici une petite macro SAS bien utile pour tout ceux qui souhaitent faire du Kernel Smoothing.