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  • Penalty, Shrinkage and Pretest Strategies

    Variable Selection and Estimation

    de S. Ejaz Ahmed ...
    Series series Mathematics and Statistics (R0)
    The objective of this book is to compare the statistical properties of penalty and non-penalty estimation strategies for some popular models. Specifically, it considers the full model, submodel, penalty, pretest and shrinkage estimation techniques for three regression models before presenting the asymptotic properties of the non-penalty estimators and their asymptotic distributional efficiency ... Leer más

    $49.99 USD

  • Matrices, Statistics and Big Data

    Selected Contributions from IWMS 2016

    Series series Springer Nature Proceedings excluding Computer Science
    This volume features selected, refereed papers on various aspects of statistics, matrix theory and its applications to statistics, as well as related numerical linear algebra topics and numerical solution methods, which are relevant for problems arising in statistics and in big data. The contributions were originally presented at the 25th International Workshop on Matrices and Statistics (IWMS ... Leer más

    $89.09 USD

  • Big and Complex Data Analysis

    Methodologies and Applications

    Edición de S. Ejaz Ahmed ...
    Series series Mathematics and Statistics (R0)
    This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Its peer-reviewed contributions showcase recent advances in variable selection, estimation and prediction strategies for a host of useful models, as well as essential new developments in the field.The continued and rapid advancement of modern technology now ... Leer más

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  • Analysis of Large and Complex Data

    Series series Springer Nature Proceedings excluding Computer Science
    This book offers a snapshot of the state-of-the-art in classification at the interface between statistics, computer science and application fields. The contributions span a broad spectrum, from theoretical developments to practical applications; they all share a strong computational component. The topics addressed are from the following fields: Statistics and Data Analysis; Machine Learning and ... Leer más

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  • New Developments in Statistical Modeling, Inference and Application

    Selected Papers from the 2014 ICSA/KISS Joint Applied Statistics Symposium in Portland, OR

    Series series Springer Nature Proceedings excluding Computer Science
    The papers in this volume represent the most timely and advanced contributions to the 2014 Joint Applied Statistics Symposium of the International Chinese Statistical Association (ICSA) and the Korean International Statistical Society (KISS), held in Portland, Oregon. The contributions cover new developments in statistical modeling and clinical research: including model development, model checking ... Leer más

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  • An Introduction to Statistical Learning

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    Series series Mathematics and Statistics (R0)
    An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant ... Leer más

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  • Python for Probability, Statistics, and Machine Learning

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    This book, fully updated for Python version 3.6+, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. All the figures and numerical results are reproducible using the Python codes provided. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes ... Leer más

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  • Regression Modeling Strategies

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  • Statistical Analysis of Network Data with R

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    Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, ... Leer más

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