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  • Advanced Markov Chain Monte Carlo Methods

    Learning from Past Samples

    Series Book 714 - Wiley Series in Computational Statistics
    Markov Chain Monte Carlo (MCMC) methods are now an indispensable tool in scientific computing. This book discusses recent developments of MCMC methods with an emphasis on those making use of past sample information during simulations. The application examples are drawn from diverse fields such as bioinformatics, machine learning, social science, combinatorial optimization, and computational ... Read more

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  • Bayesian Regression Modeling with INLA

    Series series Chapman & Hall/CRC Computer Science & Data Analysis
    INLA stands for Integrated Nested Laplace Approximations, which is a new method for fitting a broad class of Bayesian regression models. No samples of the posterior marginal distributions need to be drawn using INLA, so it is a computationally convenient alternative to Markov chain Monte Carlo (MCMC), the standard tool for Bayesian inference.Bayesian Regression Modeling with INLA covers a wide ... Read more

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  • From Statistics to Mathematical Finance

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    Series series Mathematics and Statistics (R0)
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  • Fast Electrochemical Impedance Spectroscopy

    As a Statistical Condition Monitoring Tool

    Series series Energy (R0)
    This book offers a review of electrochemical impedance spectroscopy (EIS) and its application in online condition monitoring of electrochemical devices, focusing on the practicalities of performing fast and accurate EIS. The first part of the book addresses the theoretical aspects of the fast EIS technique, including stochastic excitation signals, time-frequency signal processing, and statistical ... Read more

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    Series Book 86 - Series On Advances In Mathematics For Applied Sciences
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  • Fluctuations in Markov Processes

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