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Advances and Innovations in Statistics and Data Science

  • Book
  • © 2022

Overview

Editors:
  1. Wenqing He

    1. Department of Statistical and Actuarial Sciences, University of Western Ontario, London, Canada

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  2. Liqun Wang

    1. Department of Statistics, University of Manitoba, Winnipeg, Canada

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  3. Jiahua Chen

    1. Department of Statistics, University of British Columbia, Vancouver, Canada

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  4. Chunfang Devon Lin

    1. Department of Mathematics and Statistics, Queen’s University, Kingston, Canada

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  • Promotes methodology development in data science, statistics, and biostatistics
  • Showcases the latest work as presented at the 4th ICSA-Canada Chapter Symposium
  • Includes applications to a variety of fields, including health, economics, the social sciences, and more

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

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Table of contents (16 chapters)

  1. Front Matter

    Pages i-xvii
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  2. Methodology Development in Data Science

    1. Front Matter

      Pages 1-1
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    2. MiRNA–Gene Activity Interaction Networks (miGAIN): Integrated Joint Models of miRNA–Gene Targeting and Disturbance in Signaling Pathways

      • Henry Linder, Yuping Zhang
      Pages 3-21

    3. Robust Feature Screening for Ultrahigh-Dimensional Censored Data Subject to Measurement Error

      • Li-Pang Chen, Grace Y. Yi
      Pages 23-53

    4. Simultaneous Control of False Discovery Rate and Sensitivity Using Least Angle Regressions in High-Dimensional Data Analysis

      • Bangxin Zhao, Wenqing He
      Pages 55-68

    5. Minimum Wasserstein Distance Estimator Under Finite Location-Scale Mixtures

      • Qiong Zhang, Jiahua Chen
      Pages 69-98

    6. An Entropy-Based Comment Ranking Method with Word Embedding Clustering

      • Yuyang Zhang, Hao Yu
      Pages 99-119

    7. A Robust Approach to Statistical Quality Control for High-Dimensional Non-Normal Data

      • M. Rauf Ahmad, S. Ejaz Ahmed
      Pages 121-134

  3. Challenges in Statistical Analysis

    1. Front Matter

      Pages 135-135
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    2. Functional Linear Regression for Partially Observed Functional Data

      • Yafei Wang, Tingyu Lai, Bei Jiang, Linglong Kong, Zhongzhan Zhang
      Pages 137-158

    3. Profile Estimation of Generalized Semiparametric Varying-Coefficient Additive Models for Longitudinal Data with Within-Subject Correlations

      • Yanqing Sun, Fang Fang
      Pages 159-179

    4. Sieve Estimation of Semiparametric Linear Transformation Model with Left-Truncated and Current Status Data

      • Riyadh Rustam Al-Mosawi, Xuewen Lu
      Pages 181-224

    5. A Review of Flexible Transformations for Modeling Compositional Data

      • Michail Tsagris, Connie Stewart
      Pages 225-234

    6. Identifiability and Estimation of Autoregressive ARCH Models with Measurement Error

      • Mustafa Salamh, Liqun Wang
      Pages 235-255

    7. Modal Regression for Skewed, Truncated, or Contaminated Data with Outliers

      • Sijia Xiang, Weixin Yao
      Pages 257-273

    8. Spatial Multilevel Modelling in the Galveston Bay Recovery Study Survey

      • Mary E. Thompson, Gang Meng, Joseph Sedransk, Qixuan Chen, Rebecca Anthopolos
      Pages 275-293

    9. Efficient Experimental Design for Lasso Regression

      • Peter Chien, Xinwei Deng, Chunfang Devon Lin
      Pages 295-309

    10. A Selective Overview of Statistical Methods for Identification of the Treatment-Sensitive Subsets of Patients

      • Xinyi Ge, Yingwei Peng, Dongsheng Tu
      Pages 311-329

  4. Correction to: Identifiability and Estimation of Autoregressive ARCH Models with Measurement Error

    • Mustafa Salamh, Liqun Wang
    Pages C1-C1

  5. Back Matter

    Pages 331-332
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Keywords

About this book

This book highlights selected papers from the 4th ICSA-Canada Chapter Symposium, as well as invited articles from established researchers in the areas of statistics and data science. It covers a variety of topics, including methodology development in data science, such as methodology in the analysis of high dimensional data, feature screening in ultra-high dimensional data and natural language ranking; statistical analysis challenges in sampling, multivariate survival models and contaminated data, as well as applications of statistical methods. With this book, readers can make use of frontier research methods to tackle their problems in research, education, training and consultation.

Editors and Affiliations

  • Department of Statistical and Actuarial Sciences, University of Western Ontario, London, Canada

    Wenqing He

  • Department of Statistics, University of Manitoba, Winnipeg, Canada

    Liqun Wang

  • Department of Statistics, University of British Columbia, Vancouver, Canada

    Jiahua Chen

  • Department of Mathematics and Statistics, Queen’s University, Kingston, Canada

    Chunfang Devon Lin

About the editors

Wenqing He is Professor in the Department of Statistical and Actuarial Sciences at the University of Western Ontario, Canada. He was the Program Chair for the 4th ICSA-Canada Chpater Symposium.

Liqun Wang is Professor and Department Head in the Department of Statistics at the University of Manitoba, Canada. He is the Past-Chair of the ICSA-Canada Chapter. 

Jiahua Chen is Professor and Canada Research Chair (Tier I) in the Department of Statistics at the University of British Columbia, Canada.

Chunfang Devon Lin is Associate Professor in the Department of Mathematics and Statistics at Queen’s University, Canada. She was the local chair of the for the 4th ICSA-Canada Chapter Symposium.

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