3D Kernel Density Estimation Technology Demonstration Based on MATLAB
Kernel Density Estimation (KDE) was first proposed by Rosenblatt and Parzen. Unlike parametric methods that assume a specific distribution and parameters in advance, this method estimates the probability distribution of indicators directly from the given data sample, thus it belongs to non-parametric methods. This method is commonly applied to estimate the probability density of random … Read more