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Marcia Haskell Group

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Before talking about Quasi-Monte Carlo (QMC), a quick introduction about MonteCarlo (MC). MC methods, or MC experiments, are a broad class ofcomputational algorithms that rely on repeated random sampling to obtainnumerical results. The underlying concept is to use randomness to solveproblems that might be deterministic in principle. They are often used inphysical and mathematical problems and are most useful when it is difficult orimpossible to use other approaches. MC methods are mainly used inthree problem classes: optimization, numerical integration, and generatingdraws from a probability distribution.


For a brief introduction to the ideas behind the library, you can read theintroductory notes or the paper. Visit theinstallation page to see how you can download the packageand get started with it. You can browse the example gallery to see some of the things that you can do with seaborn,and then check out the tutorials or API referenceto find out how.

The Nuova Cronica, a 14th-century history of Florence by the Florentine banker and official Giovanni Villani, includes much statistical information on population, ordinances, commerce and trade, education, and religious facilities and has been described as the first introduction of statistics as a positive element in history,[3] though neither the term nor the concept of statistics as a specific field yet existed.

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