Kernel density estimation (KDE) and nonparametric methods form a cornerstone of contemporary statistical analysis. Unlike parametric approaches that assume a specific functional form for the ...
The Annals of Statistics, Vol. 36, No. 1 (Feb., 2008), pp. 167-198 (32 pages) We propose a test for model specification of a parametric diffusion process based on a kernel estimation of the ...
Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model. By relying directly on observed data, ...
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