High-dimensional data, such as those obtained from a gene expression microarray or second generation sequencing experiment, consist of a large number of dependent features measured on a small number of samples. One of the key problems in genomics is the identification and estimation of factors that associate with many features simultaneously. Identifying the number of factors is also important ...

In this paper, we prove an exponential rate of convergence result for a common estimator of conditional value-at-risk for bounded random variables. The bound on optimistic deviations is tighter while the bound on pessimistic deviations is more general and applies to a broader class of convex risk measures. © 2007 Elsevier B.V. All rights reserved.

The classical approach to extreme value modelling for multivariate data is to assume that the joint distribution belongs to a multivariate domain of attraction. In particular, this requires that each marginal distribution be individually attracted to a univariate extreme value distribution. The domain of attraction condition may be phrased conveniently in terms of regular variation of the joint...

Value at risk (VaR) is the standard measure of market risk used by financial institutions. Interpreting the VaR as the quantile of future portfolio values conditional on current information, the conditional autoregressive value at risk (CAViaR) model specifies the evolution of the quantile over time using an autoregressive process and estimates the parameters with regression quantiles. Utilizin...

researchers of language teaching believe that teaching method has a lot of impact on the speed and depth of learning. the importance of this is so obvious on teaching some persian language structures which are syntactically and semantically complicated. one of these structures is conditional sentences which has been considered in this study. here we tried to teach conditional sentences via both...

A considerable number of equivalent formulas defining conditional value-at-risk and expected shortfall are gathered together. Then we present a simple method to bound the conditional value-at-risk of compound Poisson loss distributions under incomplete information about its severity distribution, which is assumed to have a known finite range, mean, and variance. This important class of nonnorma...

The energy resource management (ERM) problem in today’s systems is complex and challenging due to the increasing penetration of distributed resources with uncertain behavior. Despite improvement forecasting tools, development strategies deal this uncertainty (for instance, considering Monte Carlo simulation generate a set different possible scenarios), risk associated such variable cannot be ne...