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Showing 1 - 12 of 12 results for “ying ni”
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  • Stochastic Processes, Statistical Methods, and Engineering Mathematics

    SPAS 2019, Västerås, Sweden, September 30–October 2

    Edited by Anatoliy Malyarenko, Ying Ni, Milica Rančić, Sergei Silvestrov ...
    Series series Springer Nature Proceedings excluding Computer Science
    The goal of the 2019 conference on Stochastic Processes and Algebraic Structures held in SPAS2019, Västerås, Sweden, from September 30th to October 2nd 2019, was to showcase the frontiers of research in several important areas of mathematics, mathematical statistics, and its applications. The conference was organized around the following topicsStochastic processes and modern statistical methods ... Read more

    $344.99 CAD

  • Proceedings of the Pacific Rim Statistical Conference for Production Engineering

    Big Data, Production Engineering and Statistics

    Edited by Dongseok Choi, Daeheung Jang, Tze Leung Lai, Youngjo Lee, Ying Lu, Jun Ni, Peter Qian, Peihua Qiu, George Tiao ...
    Series series Springer Nature Proceedings excluding Computer Science
    This book presents the proceedings of the 2nd Pacific Rim Statistical Conference for Production Engineering: Production Engineering, Big Data and Statistics, which took place at Seoul National University in Seoul, Korea in December, 2016. The papers included discuss a wide range of statistical challenges, methods and applications for big data in production engineering, and introduce recent ... Read more

    $115.99 CAD

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  • Data Assimilation Fundamentals

    A Unified Formulation of the State and Parameter Estimation Problem

    by Geir Evensen, Femke C. Vossepoel, Peter Jan van Leeuwen ...
    Series series Springer Textbooks in Earth Sciences, Geography and Environment
    This open-access textbook's significant contribution is the unified derivation of data-assimilation techniques from a common fundamental and optimal starting point, namely Bayes' theorem. Unique for this book is the "top-down" derivation of the assimilation methods. It starts from Bayes theorem and gradually introduces the assumptions and approximations needed to arrive at today's popular data ... Read more

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  • Applied Predictive Modeling

    by Max Kuhn, Kjell Johnson ...
    Series series Mathematics and Statistics (R0)
    This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic ... Read more

    $76.99 CAD

  • Information Geometry and Its Applications

    by Shun-ichi Amari ...
    Series series Mathematics and Statistics (R0)
    This is the first comprehensive book on information geometry, written by the founder of the field. It begins with an elementary introduction to dualistic geometry and proceeds to a wide range of applications, covering information science, engineering, and neuroscience. It consists of four parts, which on the whole can be read independently. A manifold with a divergence function is first introduced ... Read more

    $153.99 CAD

  • Data-Driven Fault Detection and Reasoning for Industrial Monitoring

    by Jing Wang, Jinglin Zhou, Xiaolu Chen ...
    Series series Engineering (R0)
    This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and ... Read more

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  • Benford's Law

    Theory and Applications

    Edited by Steven J. Miller ...
    Benford's law states that the leading digits of many data sets are not uniformly distributed from one through nine, but rather exhibit a profound bias. This bias is evident in everything from electricity bills and street addresses to stock prices, population numbers, mortality rates, and the lengths of rivers. Here, Steven Miller brings together many of the world’s leading experts on Benford’s law ... Read more

    $107.99 CAD

  • Data Processing for the AHP/ANP

    by Daji Ergu, Yong Shi, Gang Kou, Yi Peng ...
    Series series Business and Management (R0)
    The positive reciprocal pairwise comparison matrix (PCM) is one of the key components which is used to quantify the qualitative and/or intangible attributes into measurable quantities. This book examines six understudied issues of PCM, i.e. consistency test, inconsistent data identification and adjustment, data collection, missing or uncertain data estimation, and sensitivity analysis of rank ... Read more

    $64.99 CAD

  • Kernel Smoothing In Matlab: Theory And Practice Of Kernel Smoothing

    by Ivanka Horova, Jan Kolacek, Jiri Zelinka ...
    Methods of kernel estimates represent one of the most effective nonparametric smoothing techniques. These methods are simple to understand and they possess very good statistical properties. This book provides a concise and comprehensive overview of statistical theory and in addition, emphasis is given to the implementation of presented methods in Matlab. All created programs are included in a ... Read more

    $42.99 CAD

  • Introduction to Stochastic Processes with R

    by Robert P. Dobrow ...
    An introduction to stochastic processes through the use of RIntroduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability theory in the natural and social sciences. The use of simulation, by means of the popular statistical software R, makes theoretical results come alive ... Read more

    $154.99 CAD

  • The Science of Deep Learning

    by Iddo Drori ...
    The Science of Deep Learning emerged from courses taught by the author that have provided thousands of students with training and experience for their academic studies, and prepared them for careers in deep learning, machine learning, and artificial intelligence in top companies in industry and academia. The book begins by covering the foundations of deep learning, followed by key deep learning ... Read more

    $61.99 CAD

  • Geophysical Data Analysis: Discrete Inverse Theory

    MATLAB Edition

    by William Menke ...
    Series Book 45 - International Geophysics
    Since 1984, Geophysical Data Analysis has filled the need for a short, concise reference on inverse theory for individuals who have an intermediate background in science and mathematics. The new edition maintains the accessible and succinct manner for which it is known, with the addition of: - MATLAB examples and problem sets - Advanced color graphics - Coverage of new topics, including Adjoint ... Read more

    $79.99 CAD