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, ...
The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 34, No. 4 (Dec., 2006), pp. 535-561 (27 pages) The authors propose a new monotone nonparametric estimate for a regression ...
Operational risk reserves are still widely estimated using the loss distribution approach. The accuracy of the estimation depends heavily on the accuracy with which the extreme quantiles of the ...
Value-at-risk (VaR) is one of the most common risk measures used in finance. The correct estimation of VaR is essential for any financial institution, in order to arrive at the accurate capital ...
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 ...
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