Given a sample \(X_1, X_2,\dots, X_n\) from a continuous density function \(f(x)\) and distribution function \(F(x)\), \(\tilde{\eta}\) is defined by
$$\tilde{\eta}=-\frac{\sum_{i=1}^n{U_iV_i}-(n/2)\bar{U}}{\sqrt{(n/12)(\sum^{n}_{i=1}{U_i^2-n\bar{U^2}})}}$$
where
$$U_i = \hat{f}(X_i), \; V_i =F(X_i), \; \bar{U}=n^{-1}\sum_{i=1}^n U_i, \; \bar{V}=n^{-1}\sum_{i=1}^n V_i. $$
eta.w.tilde.bc
uses reflection to correct the boundary bias of kde
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