Combining local and global smoothing in multivariate density estimation
arXiv:1610.02372v17 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental improvement in density estimation methods for statistical modeling and clustering applications.
The paper tackles non-parametric multivariate density estimation by combining local and global smoothing without rigid structures, with simulation results indicating effectiveness and an application to density-based clustering.
Non-parametric estimation of a multivariate density estimation is tackled via a method which combines traditional local smoothing with a form of global smoothing but without imposing a rigid structure. Simulation work delivers encouraging indications on the effectiveness of the method. An application to density-based clustering illustrates a possible usage.