The KDE procedure performs either univariate or bivariate kernel density estimation. Statistical density estimation involves approximating a hypothesized probability density function from observed ...
Nonparametric estimation and U-statistics have emerged as vital tools in modern statistical analysis, offering robust alternatives to traditional parametric methods. Nonparametric techniques bypass ...
We consider a nonparametric method to estimate copulas, ie, functions linking joint distributions to their univariate margins. We derive the asymptotic properties of kernel estimators of copulas and ...
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