Frequently the need arises for the computer generation of variates that are exact/y distributed as 2 = max(X,, . , X.) where X,, . . . , X, form a sequence of independent identically distributed random variables. For large n the individual generation of the Xi’s is unfeasible, and the inversion-of-a-beta-variate is potentially inaccurate. In this paper, we discuss and compare the corrected inve...

Monte Carlo simulation is widely used in many fields. Unfortunately, it usually requires a large amount of computer time to obtain even moderate precision so it is necessary to apply efficiency improvement techniques. Adaptive Monte Carlo methods are specialized Monte Carlo simulation techniques where the methods are adaptively tuned as the simulation progresses. The primary focus of such techn...

Stochastic event synchrony (SES) is a recently proposed family of similarity measures. First, "events" are extracted from the given signals; next, one tries to align events across the different time series. The better the alignment, the more similar the N time series are considered to be. The similarity measures quantify the reliability of the events (the fraction of "nonaligned" events) and th...

We propose a control variate method with multiple controls to effectively reduce variances of Monte Carlo simulations for pricing European options under multifactor stochastic volatility models. Based on an application of Ito’s formula, the option price is decomposed by its discounted payoff and stochastic integrals with the appearance of gradients of the unknown option price with respect to st...

Control variates are a popular technique for reducing the variance of Monte Carlo estimates. Recent literature has enlarged the set of potentially useful control variates. Still, finding an control variate that efficiently reduces estimation error can be a challenging task for which the theoretical literature provides little guidance. In this note we show by theory and example how to construct ...

In this paper, the matrix variate ^-generalized normal distribution is introduced. Then its properties are studied. In particular, it is proved that this distribution has maximal entropy in a certain class of distributions.

Traditional approache s for storage devices simulation have been based on detailed and analytic models. However, analytic models are difficult to obtain and detailed models require a high computational cost which may be not af fordable for large scale simulations (e.g. detailed data center simulation s). In current systems like large clusters, grids, or clouds, performance and energy studies ar...

This paper presents a new control variate method for general multi-dimensional stochastic differential equations (SDEs) including jumps in order to reduce the variance of Monte Carlo method. Our control variate method is based on an asymptotic expansion technique, and does not require an explicit characteristic function of SDEs. This is an extension of previous researches using asymptotic expan...

We propose a novel hierarchical model for multitask bipartite ranking. The proposed approach combines a matrix-variate Gaussian process with a generative model for task-wise bipartite ranking. In addition, we employ a novel trace constrained variational inference approach to impose low rank structure on the posterior matrix-variate Gaussian process. The resulting posterior covariance function i...

Objective assessments of lip movement can be beneficial in many disciplines including visual speech recognition, for surgical outcome assessment in patients with cleft lip and for the rehabilitation of patients with facial nerve impairments. The aim of this study was to develop an outcome measure for lip shape during speech using statistical shape analysis techniques. Lip movements during speec...