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Advanced Statistical Methods in Data Science

  • Ding-Geng Chen
  • Jiahua Chen
  • Xuewen Lu
  • Grace Y. Yi
  • Hao Yu

Part of the ICSA Book Series in Statistics book series (ICSABSS)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Data Analysis Based on Latent or Dependent Variable Models

  3. Life Time Data Analysis

  4. Applied Data Analysis

  5. Back Matter
    Pages 219-222

About this book

Introduction

This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world.  It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a full chapter for this book in order to disseminate the findings and promote further research collaborations in this area. This timely book offers new methods that impact advanced statistical model development in big-data sciences.

Keywords

Statistical Models Degradation Models Reliability Models Accelerated Degradation Data Non-Destructive and Destructive Degradation Tests Statistical Theory and Methods Analytics

Editors and affiliations

  • Ding-Geng Chen
    • 1
  • Jiahua Chen
    • 2
  • Xuewen Lu
    • 3
  • Grace Y. Yi
    • 4
  • Hao Yu
    • 5
  1. 1.University of North Carolina Chapel Hill, NCUSA
  2. 2.Department of StatisticsUniversity of British Columbia Department of StatisticsVancouverCanada
  3. 3.Department of Mathematics and StatisticsUniversity of Calgary Department of Mathematics and StatisticsCalgary, ABCanada
  4. 4.Dept of Statistics and Actuarial ScienceUniversity of Waterloo Dept of Statistics and Actuarial ScienceWaterlooCanada
  5. 5.Dept of Statistics and Actuarial ScienceWestern University Dept of Statistics and Actuarial ScienceLondon, OntarioCanada

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-10-2594-5
  • Copyright Information Springer Science+Business Media Singapore 2016
  • Publisher Name Springer, Singapore
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-981-10-2593-8
  • Online ISBN 978-981-10-2594-5
  • Series Print ISSN 2199-0980
  • Series Online ISSN 2199-0999
  • Buy this book on publisher's site