The purpose of this paper is to compare in-sample and out-of-sample performances of three parametric and non-parametric early warning systems (EWS) for currency crises in emerging market economies ...

Scandinavian Journal of Statistics, Vol. 45, No. 2 (June 2018), pp. 217-254 (38 pages) Non-parametric generalized likelihood ratio test is a popular method of model checking for regressions. However, ...

We use influence functions as a basic tool to study unconditional nonparametric and parametric expected shortfall (ES) estimators with regard to returns data influence, standard errors and coherence.

We provide novel, high-order accurate methods for non-parametric inference on quantile differences between two populations in both unconditional and conditional settings. These quantile differences ...

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 ...

This short course will provide an overview of non-parametric statistical techniques. The course will first describe what non-parametric statistics are, when they should be used, and their advantages ...

We have performed a genome scan using 25 nuclear families consisting of right-handed parents with at least two left-handed children. Handedness was assessed as a qualitative trait using a laterality ...

Abstract: Streamflow disaggregation techniques are used to distribute a single aggregate flow value to multiple sites in both space and time while preserving distributional statistics (i.e., mean, ...