The detailed simulation of the full electron-photon cascade may require large computational resources to obtain adequate statistics in a reasonable amount of time. Therefore, the study of variance reduction techniques for this class of problem is necessary. This paper studies the impact of the quality of the importance function (with a specific focus on deterministic importance function) used f...

In this paper we employ variance ratio tests of the random walk hypothesis to investigate the interdependence of global equity markets in terms of the predictability of equity index returns and how the clustering pattern has evolved in recent years. The study is based on almost 15 years of daily returns of free float-adjusted market capitalization equity indices from 46 countries. First, we exa...

Cellular pathways involve the phosphorylation and dephosphorylation of proteins. Peptide microarrays called kinome arrays facilitate the measurement of the phosphorylation activity of hundreds of proteins in a single experiment. Analyzing the data from kinome microarrays is a multi-step process. Typically, various techniques are possible for a particular step, and it is necessary to compare and...

in this study, the spatial distribution of overwintered adults of sunn pest, eurygaster integriceps puton, was investigated by using dispersion parameters and indices, mathematical distribution, and regression techniques in rainfed wheat fields by sample size of 1 m2 in 2009 and 2010. the dispersion parameters including: mean-variance test and clumping parameter () showed that the overwintered ...

several practical problems of hypotheses testing can be under a general linear model analysis of variance which would be examined. in analysis of variance, when the response random variable y , has linear relationship with several random variables x, another important model as analysis of covariance can be used. in this paper, assuming that y is fuzzy and using dlr metric, a method for testing ...

This exercise aims at exploring different techniques for creating a random variable X according to a normal distribution with zero mean and unit variance. The methods include the use of an inverse cumulative distribution function, the Box–Muller method, the polar technique and the application of the Central Limit Theorems to uniform random variables. The normal random variables generated by the...

Ensembles of classifiers represent one of the main research directions in machine learning. Two main theories are invoked to explain the success of ensemble methods. The first one consider the ensembles in the framework of large margin classifiers, showing that ensembles enlarge the margins, enhancing the generalization capabilities of learning algorithms. The second is based on the classical b...

Abstract In this paper we introduce a new criterion in order to measure the variance and covariance risks in financial markets. In an asset allocation framework with stochastic (co)variances, we consider the possibility to invest also in variance swaps, that are assets which span the volatility as well as the co-volatility risks. We provide explicit solutions for the portfolio optimization prob...