Streamflow Generation by Boostrap Method and Skewness

A Simple Transformation Method in Skewness Reduction

Statistical analysis of non-normal data is usually more complicated than that for normaldistribution. In this paper, a simple root/power transformation technique developed by Niaki, et al [1]is extended to transform right and left skewed distributions to nearly normal. The value of theroot/power is explored such that the skewness of the transformed data becomes almost zero with anacceptable err...

Investigating and Improving the Effect of Distributed Generation on Reliability in Wind Systems by ARMA Method

The increasing development of the use of new energies has led to the widespread use of power electronics, so that electronic power converters play an important role in extracting power from renewable sources. Power electronics can convert raw energy produced from new energy into the desired power with controlled current, voltage and frequency to be used in the power grid. Restructuring of power...

Boosting boostrap FLD subspaces for multiclass problem

In this paper an ensemble feature extraction algorithm is proposed based on Adaboost.M2 for multiclass classification problem. The proposed algorithm makes no assumption about the distribution of the data and primarily performs by directly selecting the discriminant features with the minimum training error, which can overcome the main drawbacks of the traditional methods, such as Principle Comp...

Institutional Skewness Preferences and the Idiosyncratic Skewness Premium∗

This study examines whether idiosyncratic skewness preferences of institutional investors influence stock returns. On aggregate, institutions exhibit an aversion for idiosyncratic skewness but prefer systematic skewness, and in the cross-section, larger (smaller) and more (less) diversified institutions exhibit stronger (weaker) aversion for idiosyncratic skewness. The aggregate institutional p...

Skewness and Leverage