Nonparametric regression for functional data provides a flexible statistical framework for modelling relationships between a scalar response and predictors that are inherently functional in nature.

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 ...

Nonparametric methods form an important core of statistical techniques and are typically used when data do not meet parametric assumptions. Understanding the foundation of these methods, as well as ...

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 ...

Time series is data collected over time, and statistical learning is a field of statistics and machine learning that develops algorithms to model and interpret this data. Together, they use ...

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 ...