Monte Carlo methods play an important role in scientific computation, especially when problems have a vast phase space. In this chapter an introduction to the Monte Carlo method is given. Concepts such as Markov chains, detailed balance, critical slowing down, and ergodicity, as well as the Metropolis algorithm are explained. The Monte Carlo method is illustrated by numerically studying the cri...

Monte Carlo method has received significant consideration from the context of quantitative finance mainly due to its ease of implementation for complex problems in the field. Among topics of its application to finance, we address two topics: (1) optimal importance sampling for the Laplace transform of exponential Brownian functionals and (2) analysis on the convergence of quasi-regression metho...

In this work was performed a Monte Carlo Simulation for a mathematics model to experimental planning of Taguchi. The software has enabled an upgrading of the variables planning value of 54,26% of TOC, 53,28% of DQO and 6,58% of Total Phenols, that feature the importance of the method for the experimental optimizations, and thereafter reduction of experiments to be realized in the job first step.

New challenges are arising for the European electricity network due to the large scale integration of wind energy, characterized through stochastic nature and often remote location. A multivariate uncertainty analysis problem was formulated for the integration of stochastic wind energy in the European power grid, and a Monte Carlo simulation method was used to solve it. The model covers the com...

Until the last few decades, maintenance has not been considered of special importance by organisations. Thus, the number of studies that assess maintenance performance in a country is still very small, despite the relevance this area has to the level of national competitiveness. This article describes a multicriteria model integrating the fuzzy analytic hierarchy process (FAHP) with Multi-Attri...

We study the power of some exceedance rank tests against location shift and Lehman alternatives for distributions from the uniform, normal, exponential, gamma, and lognormal families. We give the corresponding power functions, obtained by Monte Carlo simulation and discuss the relative merits of the tests.

We derive a profile-likelihood confidence interval and a score based confidence interval to estimate the population prevalences, test sensitivities, and test specificities of two conditionally independent diagnostic tests when no gold standard is available. We are motivated by a real-data example on the study of the properties for two fallible diagnostic tests for bovine immunodeficiency virus....

Our emotional state influences our choices. Research on how it happens usually comes from the lab. We know rela tively little about how real world emotions affect real world settings, like financial markets. Here, we demonstrate that estimating emotions from weblogs provides novel informa tion about future stock market prices. That is, it provides information not already apparent from market da...

We show how it is possible to generate multivariate data which have moments arbitrary close to the desired ones. They are generated as linear combinations of variables with known theoretical moments. It is shown how to derive the weights of the linear combinations in both the univariate and the multivariate setting. The use in bootstrapping is discussed and examplified with an Monte Carlo simul...