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Modern Statistical Methods for Spatial and Multivariate Data

  • Norou Diawara
Book

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Amanda Working, Mohammed Alqawba, Norou Diawara
    Pages 1-30
  3. Haigang Liu, David B. Hitchcock, S. Zahra Samadi
    Pages 31-50
  4. Donald Musgrove, Derek S. Young, John Hughes, Lynn E. Eberly
    Pages 51-74
  5. Edgard M. Maboudou-Tchao
    Pages 75-93
  6. Sarah A. Janse, Katherine L. Thompson
    Pages 95-105
  7. Rajarshi Dey, Madhuri S. Mulekar
    Pages 107-129
  8. Manasi Sheth-Chandra, N. Rao Chaganty, Roy T. Sabo
    Pages 131-145
  9. Joseph Mathews, Sumen Sen, Ishapathik Das
    Pages 147-161
  10. Jennifer L. Matthews, Norou Diawara, Lance A. Waller
    Pages 163-177

About this book

Introduction

This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques.

Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field.  In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.

Keywords

optimization simulation modeling multivariate data analysis spatio-temporal techniques functional representations spatial analysis spatio-temporal analysis statistical methods poisson distribution

Editors and affiliations

  • Norou Diawara
    • 1
  1. 1.Department of Mathematics and StatisticsOld Dominion UniversityNorfolkUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-11431-2
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-030-11430-5
  • Online ISBN 978-3-030-11431-2
  • Series Print ISSN 2520-193X
  • Series Online ISSN 2520-1948
  • Buy this book on publisher's site
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